Optimal control of nonlinear processes: With applications in drugs, corruption, and terror

Optimal Control of Nonlinear Processes: With Applications in Drugs, Corruption, and Terror

Volumn , Issue , 2008, Pages 1-551

  Grass, Dieter ^a   Caulkins, Jonathan P ^b   Feichtinger, Gustav ^a   Tragler, Gernot ^a   Behrens, Doris A ^c  

^a Institute for Mathematical Methods in Economics   (Austria)

^b RAND CORPORATION   (United States)

^c UNIVERSITY OF KLAGENFURT   (Austria)

Author keywords

[No Author keywords available]

Indexed keywords

EID: 84892036294     PISSN: None     EISSN: None     Source Type: Book    
DOI: 10.1007/978-3-540-77647-5     Document Type: Book

References (427)

1. Abraham, R. H. & Shaw, C. D. (1982). Dynamics - The geometry of behavior. The Visual Mathematics Library. Santa Cruz, CA: Aerial.
2. Alemdar, N. M., Sirakaya, S., & Hüsseinov, F. (2006). Optimal time aggregation of infinite horizon control problems. Journal of Economic Dynamics and Control, 30 (4), 569-593.
3. Almeder, C., Caulkins, J. P., Feichtinger, G., & Tragler, G. (2004). An agestructured single-state drug initiation model - cycles of drug epidemics and optimal prevention programs. Socio-Economic Planning Science, 38 (1), 91- 109.
4. Almeder, C., Feichtinger, G., Sanderson, W. C., & Veliov, V. M. (2007). Prevention and medication of HIV/AIDS: The case of Botswana. Central European Journal of Operations Research, 15 (1), 47-62.
5. Andronov, A. A. (1929). Les cycles limites de Poincaŕe et la th́eorie des oscillations autoentretenues. Comptes Rendus de l'Acad́emie des Sciences de Paris, 189, 559-561.
6. Andvig, J. C. (1991). The economics of corruption: A survey. Studi economici, 43 (1), 57-94.
7. Annemans, L., Vanoverbeke, N., Tecco, J., Hariga, F., Carpentier, C., & Hartnoll, R. (2000). Macro-economic analysis of heroin markets in the EU and the impact of substitution treatment. EMCDDA Scientific Report EMCDDA/EPI/CT.99.EP.05B/2000, EMCDDA.
8. Apostol, T. M. (1977). Mathematical analysis (2nd ed.). Reading, MA: Addison-Wesley.
9. Arnold, L. (1974). Stochastic differential equations: Theory and applications. New York: Wiley.
10. Arnold, V. I. (1983). Geometrical methods in the theory of ordinary differential equations, volume 250 of Grundlehren der mathematischen Wissenschaften. New York: Springer.
11. Arnold, V. I., Goryunov, V. V., Lyashko, O. V., & Vasiliev, V. A. (1993). Dynamical system VIII: Singularity theory II - Applications, volume 39 of Encyclopaedia of Mathematical Sciences. Berlin: Springer.
12. Arquilla, J. & Ronfeldt, D. (1999). The emergence of noopolitik: Toward an American information strategy. Santa Monica, CA: RAND.
13. Arrow, K. J., Karlin, S., & Scarf, H. E. (1958). Studies in the mathematical theory of inventory and production. Stanford, CA: Stanford University Press.
14. Arrow, K. J. & Kurz, M. (1970). Public investment, the rate of return, and optimal fiscal policy. Baltimore: The Johns Hopkins University Press.
15. Arrowsmith, D. K. & Place, C. M. (1990). An introduction to dynamical systems. New York: Cambridge University Press.
16. Arutyunov, A. V. & Vinter, R. B. (2004). A simple "finite approximations" proof of the Pontryagin maximum principle under reduced differentiability hypotheses. Journal of Set Valued Analysis, 12 (1-2), 5-24.
17. Ascher, U.M., Mattheij, R.M.M., & Russell, R. D. (1995). Numerical solution of boundary value problems for ordinary differential equations. Philadelphia, PA: Society for Industrial and Applied Mathematics.
18. Aubin, J. P. & Cellina, A. (1984). Differential inclusions: Set-valued maps and viability theory. New York: Springer.
19. Aubin, J. P. & Frankowska, H. (1990). Set valued analysis. Boston: Birkḧauser.
20. Avriel, M. (1976). Nonlinear programming: Analysis and methods. Automatic computations. Englewood Cliffs, NJ: Prentice-Hall.
21. Basar, T. & Olsder, G. J. (1999). Dynamic noncooperative game theory (2nd ed.). Philadelphia: Society for Industrial and Applied Mathematics.
22. Barclay, A., Gill, P., & Rosen, J. (1997). SQP methods and their application to numerical optimal control. Numerical Analysis Report 97-3, Department of Mathematics, University of California, San Diego, La Jolla, CA.
23. Barron, E. N. & Jensen, R. (1986). The Pontryagin maximum principle from dynamic programming and viscosity solutions to first-order partial differential equations. Transactions of the American Mathematical Society, 298 (2), 635-641.
24. Barucci, E. & Gozzi, F. (1998). Investment in a vintage capital model. Research in Economics, 52 (2), 159-188.
25. Barucci, E. & Gozzi, F. (2001). Technology adoption and accumulation in a vintage capital model. Journal of Economics, 74 (1), 1-38.
26. Baveja, A., Batta, R., Caulkins, J. P., & Karwan, M. H. (1993). Modeling the response of illicit drug markets to local enforcement. Socio-Economic Planning Sciences, 27 (2), 73-89.
27. Baveja, A., Feichtinger, G., Hartl, R. F., Haunschmied, J. L., & Kort, P. M. (2000). A resource-constrained optimal control model for crackdown on illicit drug markets. Journal of Mathematical Analysis and Applications, 249 (1), 53-79.
28. Becker, G. S. (1992). Habits, addictions, and traditions. Kyklos, 45 (3), 327- 346.
29. Becker, G. S. & Murphy, K. M. (1988). A theory of rational addiction. Journal of Political Economy, 96 (4), 675-700.
30. Behrens, D. A. (1998). The US cocaine epidemic: An optimal control approach to heterogeneous consumption behavior. PhD thesis, Vienna University of Technology.
31. Behrens, D. A., Caulkins, J. P., Feichtinger, G., & Tragler, G. (2007). Incentive Stackelberg strategies for a dynamic game on terrorism. In Jørgensen, S., Quincampoix, M., & Thomas, V. L. (Eds.), Advances in dynamic game theory, volume 9 of Annals of the International Society of Dynamic Games (pp. 459-486). Boston: Birkḧauser.
32. Behrens, D. A., Caulkins, J. P., Tragler, G., & Feichtinger, G. (2000a). Memory, contagion, and capture rates: Characterizing the types of addictive behavior that are prone to repeated epidemics. Research Report 251, Institute for Mathematical Methods in Economics.
33. Behrens, D. A., Caulkins, J. P., Tragler, G., & Feichtinger, G. (2000b). Optimal control of drug epidemics: Prevent and treat - but not at the same time? Management Science, 46 (3), 333-347.
34. Behrens, D. A., Caulkins, J. P., Tragler, G., & Feichtinger, G. (2002). Why present-oriented societies undergo cycles of drug epidemics. Journal of Economic Dynamics and Control, 26 (6), 919-936.
35. Behrens, D. A., Caulkins, J. P., Tragler, G., Haunschmied, J. L., & Feichtinger, G. (1999). A dynamic model of drug initiation: Implications for treatment and drug control. Mathematical Biosciences, 159 (1), 1-20.
36. Behrens, D. A. & Neck, R. (2007). OPTGAME: An algorithm approximating solutions for multi-player difference games. In Elleithy, K. (Ed.), Advances and innovations in systems, computing sciences and software engineering (pp. 93-98). Dodrecht: Springer.
37. Bell, D. J. & Jacobson, D. H. (1975). Singular optimal control problems, volume 117 of Mathematics in Science and Engineering. London: Academic.
38. Bellman, R. (1957). Dynamic programming. Princeton, NJ: Princeton University Press.
39. Bellman, R. (1961). Adaptive control processes: A guided tour. Princeton, NJ: Princeton University Press.
40. Bensoussan, A., Hurst Jr., E. G., & Naslund, B. (1974). Management applications of modern control theory. Amsterdam: North-Holland.
41. Bensoussan, A. & Lions, J. L. (1982). Application of variational inequalities in stochastic control. Amsterdam: North-Holland.
42. Bensoussan, A. & Lions, J. L. (1984). Impulse control and quasi-variational inequalities. Paris: Bordas.
43. Bensoussan, A., Nissen, G., & Tapiero, C. S. (1975). Optimum inventory and product quality control with deterministic and stochastic deterioration - An application of distributed parameter control. IEEE Transactions on Automatic Control, 20 (3), 407-412.
44. Bertsekas, D. P. (2005). Dynamic programming and optimal control (3rd ed.).Belmont, MA: Athena Scientific.
45. Bertsekas, D. P., Nedic, A., & Ozdaglar, A. E. (2003). Convex analysis and optimization. Belmont, MA: Athena Scientific.
46. Bertsekas, D. P., Ozdaglar, A. E., & Tseng, P. (2006). Enhanced Fritz John conditions for convex programming. SIAM Journal on Optimization, 16 (3), 766-797.
47. Beyn, W. J., Pampel, T., & Semmler, W. (2001). Dynamic optimization and Skiba sets in economic examples. Optimal Control Applications and Methods, 22 (5-6), 251-280.
48. Blaquière, A. (1985). Impulsive optimal control with finite or infinite time horizon. Journal of Optimization Theory and Applications, 46 (4), 431-439.
49. Bliss, G. A. (1925). Calculus of variations. Number 1 in Carus Mathematical Monograph. Chicago: Open Court.
50. Bliss, G. A. (1946). Lectures on the calculus of variations. Chicago: University of Chicago Press.
51. Boltyanski, V. G. (1994). The maximum principle: How it came to be. Report 526, Mathematisches Institut, Technische Universiẗat, M̈unchen.
52. Boltyanski, V. G., Gamkrelidze, R. V., & Pontryagin, L. S. (1956). On the theory of optimal processes. Doklady Akademii Nauk SSSR, 110 (1), 7-10.
53. Booß-Bavnbek, B. & Høyrup, J. (Eds.). (2003). Mathematics and war. Basel: Birkḧauser.
54. Boucekkine, R., Saglam, H. C., & Vallée, T. (2004). Technology adoption under embodiment: A two-stage optimal control approach. Macroeconomic dynamics, 8(2), 250-271.
55. Breakwell, J. V. (1964). Minimum impulse transfer. In Szebehely, V. G. (Ed.), Celestial mechanics and astrodynamics. Progress in astronautics and aeronautics, volume 14 (pp. 583-589). New York: Academic.
56. Breitner, M. (2005). The genesis of differential games in light of Isaacs' contributions. Journal of Optimization Theory and Applications, 124 (3), 523-559.
57. Brito, P. M. B. (1999). Local dynamics for optimal control problems of threedimensional ODE systems. Annals of Operations Research, 89 (0), 195-214.
58. Brock, W. A. (1983). Pricing, predation and entry barriers in regulated industries. In D. S. Evans (Ed.), Breaking Up Bell (pp. 191-229). New York: North-Holland.
59. Brock, W. A. & Dechert, W. D. (1983). The generalized maximum principle. Working Paper 8316, Social Science Research Institute, University of Wisconsin.
60. Brock, W. A. & Dechert, W. D. (1985). Dynamic Ramsey pricing. International Economic Review, 26 (3), 569-591.
61. Brock, W. A. & Malliaris, A. G. (1989). Differential equations, stability and chaos in dynamic economics. Amsterdam: North-Holland.
62. Brock, W. A. & Starrett, D. (1999). Nonconvexities in ecological management problems. Working Paper, University of Wisconsin.
63. Brokate, M. (1985). Pontryagin's principle for control problems in agedependent population dynamics. Journal of Mathematical Biology, 23 (1), 75-101.
64. Bryson, A. E. & Ho, Y. C. (1975). Applied optimal control: Optimization, estimation, and control. New York: Hemisphere Publishing.
65. Bultmann, R. (2007). The impact of supply shocks on optimal dynamic drug policies. Master's thesis, Vienna University of Technology.
66. Bultmann, R., Caulkins, J. P., Feichtinger, G., & Tragler, G. (2007). How should drug policy respond to market disruptions? forthcoming in Contemporary Drug Problems.
67. Bultmann, R., Caulkins, J. P., Feichtinger, G., & Tragler, G. (2008). Modeling supply shocks in optimal control models of illicit drug consumption. forthcoming in Lecture Notes in Computer Science, 4818, 275-282.
68. Bushaw, D. W. (1952). Differential equations with a discontinuous forcing term. PhD thesis, Princeton University, Department of Mathematics.
69. Buskens, C. & Maurer, H. (2000). SQP-methods for solving optimal control problems with control and state constraints: Adjoint variables, sensitivity analysis and real-time control. Journal of Computational and Applied Mathematics, 120 (1), 85-108.
70. Byrd, W. & Ward, C. (2004). Drugs and development in Afghanistan. Social Development Papers - Conflict Prevention & Reconstruction 18, TheWorld Bank.
71. Canon, M. D., Cullum, C. D., & Polak, E. (1970). Theory of optimal control and mathematical programming. New York: McGraw-Hill Book Company.
72. Caputo, M. R. (2005). Foundations of dynamic economic analysis. Cambridge, UK: Cambridge University Press.
73. Caratheodory, C. (1926). Uber das Schwarzsche Lemma bei analytischen Funktionen von zwei komplexen Ver̈anderlichen. Mathematische annalen, 97 (1), 76-98.
74. Carathéodory, C. (1935). Exemples particuliers et th́eorie ǵeńerale dans le calcul des variations. L'Enseigement Math́ematique, 34, 255-261.
75. Carlson, D. A., Haurie, A., & Leizarowitz, A. (1991). Infinite horizon optimal control: deterministic and stochastic systems (2nd ed.). New York: Springer.
76. Caroff, N. & Frankowska, H. (1996). Conjugate points and shocks in nonlinear optimal control. Transactions of the American Mathematical Society, 348 (8), 3133-3153.
77. Carr, J. (1981). Applications of center manifold theory. New York: Springer.
78. Cass, D. (1965). Optimum growth in an aggregative model of capital accumulation. Review of Economic Studies, 32 (3), 233-240.
79. Cass, D. (1966). Optimum growth in an aggregative model of capital accumulation: A turnpike theorem. Econometrica, 34 (4), 833-850.
80. Castillo-Chavez, C. & Song, B. (2003).Models of the transmission dynamics of fanatic behaviors. In Banks, H. T. & Castillo-Chavez, C. (Eds.), Bioterrorism: Mathematical modeling applications in Homeland Security, volume 28 of Frontiers in applied mathematics (pp. 155-172). Philadelphia: Society for Industrial and Applied Mathematics.
81. Caulkins, J. P. (1993). Local drug markets' response to focused police enforcement. Operations Research, 41 (5), 848-863.
82. Caulkins, J. P. (1996). What does mathematical modeling tell us about harm reduction? Drug and Alcohol Review, 15 (3), 231-235.
83. Caulkins, J. P. (2005). Models pertaining to how drug policy should vary over the course of a drug epidemic. In Lingren, B. & Grossman, M. (Eds.), Substance use: Individual behavior, social interactions, markets, and politics, volume 16 of Advances in Health Economics and Health Services Research (pp. 407-439). Amsterdam: Elsevier.
84. Caulkins, J. P., Behrens, D. A., Knoll, C., Tragler, G., & Zuba, D. (2004). Markov chain modeling of initiation and demand: The case of the US cocaine epidemic. Health Care Management Science, 7(4), 319-329.
85. Caulkins, J. P., Dietze, P., & Ritter, A. (2007). Dynamic compartmentalmodel of trends in Australian drug use. Health Care Management Science, 10 (2), 151-162.
86. Caulkins, J. P., Dworak, M., Feichtinger, G., & Tragler, G. (2000). Priceraising drug enforcement and property crime: A dynamic model. Journal of Economics, 71 (3), 227-253.
87. Caulkins, J. P., Feichtinger, G., Gavrila, C., Greiner, A., Haunschmied, J. L., Kort, P. M., & Tragler, G. (2006). Dynamic cost-benefit analysis of drug substitution programs. Journal of Optimization Theory and Applications, 128 (2), 279-294.
88. Caulkins, J. P., Feichtinger, G., Grass, D., & Tragler, G. (2007a). Bifurcating DNS thresholds in a model of organizational bridge building. Journal of Optimization Theory and Applications, 133 (1), 19-35.
89. Caulkins, J. P., Feichtinger, G., Grass, D., & Tragler, G. (2007b). Optimal control of terrorism and global reputation. In submission.
90. Caulkins, J. P., Feichtinger, G., Johnson, M., Tragler, G., & Yegorov, Y. (2005). Skiba thresholds in a model of controlled migration. Journal of Economic Behavior & Organization, 57 (4), 490-508.
91. Caulkins, J. P., Feichtinger, G., Tragler, G., & Veliov, V. M. (2007). Cycles of violence: A dynamic control analysis. European Journal of Operational Research, 181 (1), 350-361.
92. Caulkins, J. P., Feichtinger, G., Tragler, G., & Wallner, D. (2007). When in a drug epidemic should the policy objective switch from use reduction to harm reduction? In submission.
93. Caulkins, J. P., Gragnani, A., Feichtinger, G., & Tragler, G. (2006). High and low frequency oscillations in drug epidemics. International Journal of Bifurcation and Chaos, 16 (11), 3275-3289.
94. Caulkins, J. P., Hartl, R. F., Kort, P. M., & Feichtinger, G. (2007). Explaining fashion cycles: Imitators chasing innovators in product space. Journal of Economic Dynamics and Control, 31 (5), 1535-1556.
95. Caulkins, J. P., Hartl, R. F., Tragler, G., & Feichtinger, G. (2001). Why politics makes strange bedfellows: Dynamic model with DNS curves. Journal of Optimization Theory and Applications, 111 (2), 1573-2878.
96. Caulkins, J. P., Rydell, C. P., Peter, C., Everingham, S. S., James, C., & Shawn, B. (1999). An ounce of prevention, a pound of uncertainty: The cost-effectiveness of school-based drug prevention programs. Santa Monica, CA: RAND.
97. Cesari, L. (1983). Optimization - Theory and applications, problems with ordinary differential equations. New York: Springer.
98. Chander, P. & Wilde, L. (1992). Corruption in tax administration. Journal of Public Economics, 49 (3), 333-349.
99. Chiang, A. C. (1992). Elements of dynamic optimization. New York: McGraw- Hill.
100. Chiarella, C. (1988). The cobweb model: Instability and the onset of chaos. Economic modelling, 5(4), 377-384.
101. Chillingworth, D. R. J. (1976). Differential topology with a view to applications. London: Pitman.
102. Clarke, F. H. (1976). The maximum principle under minimal hypotheses. SIAM Journal on Control and Optimization, 14 (6), 1078-1091.
103. Clarke, F. H. (1983). Optimization and nonsmooth analysis. New York: Wiley.
104. Clarke, F. H., Ledyaev, Y., Stern, R. J., & Wolenski, P. R. (1998). Nonsmooth analysis and control theory. New York: Springer.
105. Crandall, M. G. & Lions, P. L. (1983). Viscosity solutions of Hamilton-Jacobi equations. Transactions of the American Mathematical Society, 277 (1), 1- 42.
106. Cullum, J. (1969). Discrete approximations to continuous optimal control problems. SIAM Journal on Control and Optimization, 7(1), 32-49.
107. Dawid, H. & Feichtinger, G. (1996). Optimal allocation of drug control efforts: A differential game analysis. Journal of Optimization Theory and Applications, 91 (2), 279-297.
108. Dawid, H., Feichtinger, G., & Novak, A. J. (2002). Extortion as an obstacle to economic growth: A dynamic game analysis. European Journal of Political Economy, 18 (3), 499-516.
109. de Hoog, F. R. & Weiss, R. (1980). An approximation theory for boundary value problems on infinite intervals. Computing, 24 (2-3), 227-239.
110. Dechert, W. D. (1983). Increasing returns to scale and the reverse flexible accelerator. Economics Letters, 13 (1), 69-75.
111. Dechert, W. D. & Nishimura, K. (1983). A complete characterization of optimal growth paths in an aggregated model with a non-concave production function. Journal of Economic Theory, 31 (2), 332-354.
112. Deissenberg, C., Feichtinger, G., Semmler, W., & Wirl, F. (2004). Multiple equilibria, history dependence, and global dynamics in intertemporal optimization models. InW. A. Barnett, C. Deissenberg, & G. Feichtinger (Eds.), Economic Complexity: Non-linear Dynamics, Multi-agents Economies and Learning (pp. 91-122). Amsterdam: Elsevier Science.
113. Derzko, N. A., Sethi, S. P., & Thompson, G. L. (1980). Distributed parameter systems approach to the optimal cattle ranching problem. Optimal Control Applications and Methods, 1(1), 3-10.
114. Dietz, K. (1997). Introduction to McKendrick (1926), Applications of mathematics to medical problems. In S. Kotz & N. L. Johnson (Eds.), Breakthroughs in Statistics (pp. 17-26). Berlin: Springer.
115. Dixit, A. K. & Pindyck, R. S. (1994). Investment under uncertainty. Princeton: Princeton University Press.
116. Dockner, E. J. (1985). Local stability analysis in optimal control problems with two state variables. In Feichtinger, G. (Ed.), Optimal control theory and economic analysis 2 (pp. 89-103). Amsterdam: North-Holland.
117. Dockner, E. J. & Feichtinger, G. (1991). On the optimality of limit cycles in dynamic economic systems. Journal of Economics, 53 (1), 31-50.
118. Dockner, E. J. & Feichtinger, G. (1993). Cyclical consumption patterns and rational addiction. The American Economic Review, 83 (1), 256-263.
119. Dockner, E. J., Feichtinger, G., & Jørgensen, S. (1985). Tractable classes of nonzero-sum open-loop Nash differential games: Theory and examples. Journal of Optimization Theory and Applications, 45 (2), 179-197.
120. Dockner, E. J., Jørgensen, S., Long, N. V., & Sorger, G. (2000). Differential games in economics and management science. Cambridge: Cambridge University Press.
121. Dockner, E. J. & Long, N. V. (1993). International pollution control: Cooperative versus non-cooperative strategies. Journal of Environmental Economics and Management, 25 (1), 13-29.
122. Dolcetta, I. C. (1983). On a discrete approximation of the Hamilton-Jacobi equation of dynamic programming. Applied Mathematics and Optimization, 10 (1), 367-377.
123. Dorfman, R. (1969). An economic interpretation of optimal control theory. American Economic Review, 59 (5), 817-831.
124. Dreyfus, S. E. (1965). Dynamic programming and the calculus of variations. New York: Academic.
125. Dubovickii, A. J. & Miljutin, Y. A. (1965). Extremum problems in the presence of restrictions. Computational Mathematics and Mathematical Physics, 5(3), 1-80.
126. Easterlin, R. A. (1961). The american baby boom in historical perspective. The American Economic Review, 51 (5), 869-911.
127. Ehrlich, I. (2000). Uncertain lifetime, life protection, and the value of life saving. Journal of Health Economics, 19 (3), 341-367.
128. Ehtamo, H. & Hämäläinen, R. P. (1986). On affine incentives for dynamic decision problems. In Ba̧sar, T. (Ed.), Dynamic games and applications in economics (pp. 46-63). Berlin: Springer.
129. Ehtamo, H. & Hämäläinen, R. P. (1993). A cooperative incentive equilibrium for a resource management problem. Journal of Economic Dynamics and Control, 17 (4), 659-678.
130. El Ouardighi, F. (2002). The dynamics of cooperation. International Game Theory Review, 4(1), 1-16.
131. Engwerda, J. C. (2005). LQ Dynamic optimization and differential games. New York: Wiley.
132. Evans, G. C. (1924). The dynamics of monopoly. American Mathematical Monthly, 31 (2), 75-83.
133. Everingham, S. S. & Rydell, C. P. (1994). Modeling the demand for cocaine. RAND Monograph Report.
134. Everingham, S. S., Rydell, C. P., & Caulkins, J. P. (1995). Cocaine consumption in the U. S.: Estimating past trends and future scenarios. Socio- Economic Planning Sciences, 29 (4), 305-314.
135. Falcone, M. (1987). A numerical approach to the infinite horizon problem of deterministic control theory. Applied Mathematics and Optimization, 15 (1), 1-13.
136. Farkas, J. (1902). Theorie der einfachen Ungleichungen. Journal f̈ur die reine und angewandte Mathematik, 124, 1-27.
137. Feichtinger, G. (1982a). The Nash solution of a maintenance-production differential game. European Journal of Operations Research, 10 (2), 165-172.
138. Feichtinger, G. (1982b). Optimal policies for two firms in a noncooperative research project. In Feichtinger, G. (Ed.), Optimal control theory and economic analysis (pp. 373-397). Amsterdam: North-Holland.
139. Feichtinger, G. (1983). A differential games solution to a model of competition between a thief and the police. Management Science, 29 (6), 686-699.
140. Feichtinger, G. (1987). Intertemporal optimization of wine consumption at a party: An unusual optimal control model. In Gandolfo, G. & Monzano, F. (Eds.), Keynesian Theory Planning Models and Quantitive Economics. Essays in Memory of Vittorio Marrama, volume II (pp. 777-797). Universita Degli Studi di Roma "La Sapienza".
141. Feichtinger, G. (1992). Hopf bifurcation in an advertising diffusion model. Journal of Economic Behavior & Organization, 17 (3), 401-411.
142. Feichtinger, G. (2001). Environmental policy design and the economics of crime: Some analogies in intertemporal optimization. In P. Kischka, U. Leopold-Wildburger, R. H. Moring, & F. J. Radermacher (Eds.), Models, Methods and Decision Support for Management (pp. 23-48). Heidelberg: Physica.
143. Feichtinger, G., Grienauer, W., & Tragler, G. (2002). Optimal dynamic law enforcement. European Journal of Operational Research, 141 (1), 58-69.
144. Feichtinger, G. & Hartl, R. F. (1986). Optimale Kontrolle okonomischer Prozesse: Anwendungen des Maximumprinzips in den Wirtschaftswissenschaften. Berlin: Walter de Gruyter.
145. Feichtinger, G., Hartl, R. F., Kort, P. M., & Novak, A. J. (2001). Terrorism control in the tourism industry. Journal of Optimization Theory and Applications, 108 (2), 283-296.
146. Feichtinger, G., Hartl, R. F., Kort, P. M., & Veliov, V. M. (2005). Environmental policy, the Porter hypothesis and the composition of capital: Effects of learning and technological progress. Journal of Environmental Economics and Management, 50 (2), 434-446.
147. Feichtinger, G., Hartl, R. F., Kort, P. M., & Veliov, V. M. (2006a). Anticipation effects of technological progress on capital accumulation: A vintage capital approach. Journal of Economic Theory, 126 (1), 143-164.
148. Feichtinger, G., Hartl, R. F., Kort, P. M., & Veliov, V. M. (2006b). Capital accumulation under technological progress and learning: A vintage capital approach. European Journal of Operations Research, 172 (1), 293-310.
149. Feichtinger, G., Hartl, R. F., Kort, P. M., & Wirl, F. (2001). The dynamics of a simple relative adjustment cost framework. German Economic Review, 2(3), 255-268.
150. Feichtinger, G., Hartl, R. F., & Sethi, S. P. (1994). Dynamic optimal control models in advertising: Recent developments. Management Science, 40 (2), 195-226.
151. Feichtinger, G., Kistner, K. P., & Luhmer, A. (1988). A dynamic model of intensity splitting. Zeitschrift fur Betriebswirtschaft, 11, 1242-1258. in German.
152. Feichtinger, G. & Mehlmann, A. (1986). Planning the unusual: Applications of control theory to nonstandard problems. Acta Applicandae Mathematicae, 7(1), 79-102.
153. Feichtinger, G. & Novak, A. J. (2008). Terror and counter-terror operations: A differential game with a cyclical Nash solution. Forthcoming in Journal of Optimization Theory and Applications.
154. Feichtinger, G., Prskawetz, A., & Veliov, V. M. (2004). Age-structured optimal control in population economics. Theoretical Population Biology, 65 (4), 373-387.
155. Feichtinger, G. & Sorger, G. (1986). Optimal oscillations in control models: How can constant demand lead to cyclical production? Operations Research Letters, 5(6), 277-281.
156. Feichtinger, G. & Steindl, A. (2006). DNS curves in a production/inventory model. Journal of Optimization Theory and Applications, 128 (2), 295-308.
157. Feichtinger, G., Tragler, G., & Veliov, V. M. (2003). Optimality conditions for age-structured control systems. Journal of Mathematical Analysis and Applications, 288 (1), 47-68.
158. Feichtinger, G., Tsachev, T., & Veliov, V. M. (2004). Maximum principle for age and duration structured systems: A tool for optimal prevention and treatment of HIV. Mathematical Population Studies, 11 (1), 3-28.
159. Feichtinger, G. & Veliov, V. M. (2007). On a distributed control problem arising in dynamic optimization of a fixed-size population. SIAM Journal of Optimization, 18 (3), 980-1003.
160. Feichtinger, G. & Wirl, F. (1991). Politico-economic cycles of regulation and deregulation. European Journal of Political Economy, 7(4), 469-485.
161. Feichtinger, G. & Wirl, F. (1994). On the stability and potential cyclicity of corruption in governments subject to popularity constraints. Mathematical Social Sciences, 28 (2), 113-131.
162. Feichtinger, G. & Wirl, F. (2000). Instabilities in concave, dynamic, economic optimization. Journal of Optimization Theory and Applications, 107 (2), 275-286.
163. Feldbaum, A. A. (1965). Optimal control systems. New York: Academic.
164. Fent, T., Feichtinger, G., & Tragler, G. (2002). A dynamic game of offending and law enforcement. International Game Theory Review, 4(1), 71-89.
165. Fent, T., Feichtinger, G., & Zalesak, M. (1999). Optimal offending in view of the offender's criminal record. Central European Journal of Operations Research, 7(2), 111-177.
166. Fernandez, C. E. & Zuazua, E. (2003). Control theory: History, mathematical achievements and perspectives. Boletin SEMA, 26, 79-140.
167. Filar, J. A. & Vrieze, K. (1997). Competitive markov decision processes. New York: Springer.
168. Fisher, R. A. (1930). The genetical theory of natural selection. Oxford: Clarendon.
169. Fisher, W. H. & Hof, F. X. (2005). Status seeking in the small open economy. Journal of Macroeconomics, 27 (2), 209-232.
170. Fleming, W. H. (1988). Future directions in control theory: A mathematical perspective. Society for Industrial and Applied Mathematics.
171. Fleming, W. H. & Rishel, R. W. (1975). Deterministic and stochastic optimal control. New York: Springer.
172. Fletcher, R. (1987). Practical methods of optimization (2nd ed.). Chichester: Wiley.
173. Forman, P. & Sanchez-Ron, J. M. (Eds.). (1996). National military establishments and the advancement of science: Studies in twentieth century history. Dordrecht: Kluwer.
174. Forster, B. A. (1977). On a state variable optimal control problem: Consumption-pollution trade-offs. In J. D. Pitchford & S. J. Turnovsky (Eds.), Applications of Control Theory to Economic Analysis (pp. 35-56). Amsterdam: North-Holland.
175. Fraser-Andrews, G. (1999). A multiple-shooting technique for optimal control. Journal of Optimization Theory and Applications, 102 (2), 299-313.
176. Friedlander, G. & Joshi, M. (1998). Introduction to the theory of distributions (2nd ed.). Cambridge: Cambridge Universtiy Press.
177. Friedrich, C. J. (1972). The pathology of politics, violence, betrayal, corruption, secrecy, and propaganda. New York: Harper & Row.
178. Frueh, D. P., Ito, T., Li, J. S., Wagner, G., Glaser, S. J., & Khaneja, N. (2005). Sensitivity enhancement in NMR of macromolecules by application of optimal control theory. Journal of Biomolecular NMR, 32 (1), 23-30.
179. Fudenberg, D. & Tirole, J. (1991). Game theory. Cambridge, MA: MIT.
180. Gaimon, C. & Thompson, G. L. (1984). A distributed parameter cohort personnel planning model that uses cross-sectional data. Management Science, 30 (6), 750-764.
181. Gamkrelidze, R. V. (1978). Principles of optimal control theory. New York: Plenum.
182. Gardiner, K. L. & Schreckengost, R. C. (1987). A system dynamics model for estimating heroin imports into the United States. System Dynamics Review, 3(1), 8-27.
183. Gavrila, C., Feichtinger, G., Tragler, G., Hartl, R. F., & Kort, P. M. (2005). History-dependence in a rational addiction model. Mathematical Social Sciences, 49 (3), 273-293.
184. Girsanov, I. V. (1972). Lectures on mathematical theory of extremum problems. New York: Springer.
185. Goetz, R. U. & Zilberman, D. (2000). The dynamics of spatial pollution. Journal of Economic Dynamics and Control, 24 (1), 143-163.
186. Goetz, R. U. & Zilberman, D. (2007). The economics of land-zoning: The dynamic approach. Optimal Control Applications and Methods, 28 (1), 21- 43.
187. Goffe, W. L. (1993). A user's guide to the numerical solution of two-point boundary value problems arising in continuous time dynamic economic models. Computational Economics, 6(3-4), 249-255.
188. Goldstine, H. H. (1980). A history of the calculus of variations from the 17th through the 19th century. New York: Springer.
189. Golub, G. & van Loan, C. (1996). Matrix computations (3rd ed.). Baltimore: The Johns Hopkins University Press.
190. Gordon, H. S. (1954). The economic theory of a common-property resource: The fishery. The Journal of Political Economy, 62 (2), 124-142.
191. Gould, J. P. (1970). Diffusion process and optimal advertising policy. In Phelps, E. S. (Ed.), Microeconomic foundations of employment and inflation theory (pp. 338-368). London: Macmillan.
192. Grass, D., Hartl, R. F., & Kort, P. M. (2007). Capital accumulation and embodied technological progress. Working paper.
193. Großlicht, F. (2003). Optimal dynamic allocation of prevention and treatment in a model of the australian heroin epidemic. Master's thesis, Vienna University of Technology.
194. Grossman, M. (1972). On the concept of health capital and the demand for health. Journal of Political Economy, 80 (2), 223-255.
195. Bellman equation. Numerische Mathematik, 75 (3), 319-337.
196. Guckenheimer, J. & Holmes, P. (1983). Nonlinear oscillations, dynamical systems, and bifurcation of vector fields. New York: Springer.
197. Hadeler, K. P. (Ed.). (1984). Perspectives in mathematics, chapter spread and age structure in epidemic models (pp. 295-320). Basel: Birkḧauser.
198. Hadley, G. & Kemp, M. C. (1971). Variational methods in economics. London: North-Holland.
199. Hager, M., Neck, R., & Behrens, D. A. (2001). Solving dynamic
200. Halkin, H. (1974). Necessary conditions for optimal control problems with infinite horizons. Econometrica, 42 (2), 267-272.
201. Halkin, H. & Neustadt, L. W. (1966). General necessary conditions for optimization problems. Proceedings of the National Academy of Sciences of the United States of America, 56 (4), 1066-1071.
202. Hall, R. E. & Jones, C. I. (2007). The value of life and the rise in health spending. Quarterly Journal of Economics, 122 (1), 39-72.
203. Hartl, R. F. (1984). Optimal dynamic advertising policies for hereditary processes. Journal of Optimization Theory and Applications, 43 (1), 51-72.
204. Hartl, R. F. (1987). A simple proof of the monotonicity of the state trajectories in autonomous control problems. Journal of Economic Theory, 40 (1), 211- 215.
205. Hartl, R. F., Kort, P. M., & Feichtinger, G. (2003). Offense control taking into account heterogeneity of age. Journal of Optimization Theory and Applications, 116 (3), 591-620.
206. Hartl, R. F., Kort, P. M., Feichtinger, G., &Wirl, F. (2004).Multiple equilibria and thresholds due to relative investment costs. Journal of Optimization Theory and Applications, 123 (1), 49-82.
207. Hartl, R. F. & Sethi, S. P. (1983). A note on the free terminal time transversality condition. Mathematical Methods of Operations Research, 27 (1), 203- 208.
208. Hartl, R. F. & Sethi, S. P. (1984). Optimal control of a class of systems with continuous lags: Dynamic programming approach and economic interpretations. Journal of Optimization Theory and Applications, 43 (1), 73-88.
209. Hartl, R. F., Sethi, S. P., & Vickson, R. G. (1995). A survey of the maximum principles for optimal control problems with state constraints. SIAM Review, 37 (2), 181-218.
210. Hartman, P. (1982). Ordinary differential equations (2nd ed.). Basel: Birkḧauser.
211. Harwood, H. J. & Myers, T. G. (Eds.). (2003). Behavioral, ethical, legal, and social implications of immunotherapies and depot medications for treating drug addiction. Washington, DC: National Academy.
212. Hassard, B. D., Kazarinoff, N. D., & Wan, Y. H. (1981). Theory and application of Hopf bifurcation. Number 41 in London Mathematical Society Lecture Note Series. London: Cambridge University Press.
213. Haunschmied, J. L., Feichtinger, G., Kort, P. M., & Hartl, R. F. (2005). Keeping up with the techonlogy pace: A DNS-curve and a limit cycle in a technology investment decision problem. Journal of Economic Behavior and Organization, 57 (4), 509-529.
214. Haunschmied, J. L., Kort, P. M., Hartl, R. F., & Feichtinger, G. (2003). A DNS-curve in a two-state capital accumulation model: A numerical analysis. Journal of Economic Dynamics and Control, 27 (4), 701-716.
215. Haurie, A. (2001). A historical perspective on cooperative differential games. In Altman, E. & Pourtallier, O. (Eds.), Advances in dynamic games andapplications, volume 6 of Annals of the international society of dynamic games (pp. 19-30). Boston: Birkḧauser.
216. Haurie, A., Sethi, S. P., & Hartl, R. F. (1984). Optimal control of an agestructured population model with applications to social services planning. Large Scale Systems, 6, 133-158.
217. Hestenes, M. R. (1950). A general problem in the calculus of variations with applications to paths of least time. RAND Research Memorandum, 100. RM-100.
218. Hestenes, M. R. (1965). On variational theory and optimal control theory. SIAM Journal on Control and Optimization, A3, 23-48.
219. Hillman, A. L. & Katz, E. (1987). Hierarchical structure and the social costs of bribes and transfers. Journal of Public Economics, 34 (2), 129-142.
220. Hirsch, M. W. & Smale, S. (1974). Differential equations, dynamical systems, and linear algebra. New York: Academic.
221. Hirsch, M. W., Smale, S., & Devaney, R. (2002). Differential equations, dynamical systems and an introduction to chaos (2nd ed.). Oxford: Elsevier.
222. Ho, Y. C. (1970). Differential games, dynamic optimization, and generalized control theory. Journal of Optimization Theory and Applications, 6(3), 1573-2878.
223. Hof, F. X. & Wirl, F. (2008).Wealth induced multiple equilibria in small open economy versions of the Ramsey model. Forthcoming in Homo Oeconomicus.
224. Hofbauer, J. & Sigmund, K. (1988). The theory of evolution and dynamical systems. Cambridge, U.K.: Cambridge University Press.
225. Holling, C. S. (1959). The components of predation as revealed by a study of small mammal predation of the European pine sawfly. Canadian Entomologist, 91, 293-320.
226. Homer, J. B. (1993a). Projecting the impact of law enforcement on cocaine prevalence: A system dynamics approach. Journal of Drug Issues, 23 (2), 281-295.
227. Homer, J. B. (1993b). A system dynamics model for cocaine prevalence estimation and trend projection. Journal of Drug Issues, 23 (2), 251-279.
228. Hommes, C. H. (1991). Chaotic Dynamics in Economic Models: Some Simple Case-Studies. Groningen: Wolters-Noordhoff.
229. Hopf, E. (1943). Abzweigung einer periodischen Losung von einer stationaren Losung eines Differentialsystems. Berichte der Sächsischen Akademie der Wissenschaften, Leipzig, 95, 3-22.
230. Hotelling, H. (1931). The economics of exhaustible resources. Journal of Political Economy, 39 (2), 137-175.
231. Høyrup, J. (1994). In measure, number, and weight. Studies in mathematics and culture. New York: State University of New York Press.
232. Huisman, K. J. (2001). Technology investment: A game theoretic real options approach. Dordrecht: Kluwer Academic.
233. Intriligator, M. D. (1971). Mathematical optimization and economic theory. Englewood-Cliffs: Prentice-Hall.
234. Ioffe, A. D. & Tichomirov, V. M. (1979). Theory of extremal problems, volume 6 of Studies in mathematics and its applications. Amsterdam: North- Holland.
235. Isaacs, R. (1965). Differential games: A mathematical theory with applications to warfare and pursuit, control and optimization. New York: Wiley.
236. John, F. (1948). Extremum problems with inequalities as subsidiary conditions. In Friedrichs, K. O., Neugebauer, O. E., & Stoker, J. J. (Eds.), Studies and Essays presented to Richard Courant on his 60th Birthday (pp. 187-204). New York: Interscience.
237. Jørgensen, S. & Zaccour, G. (2004). Differential games in marketing. Boston: Kluwer Academic.
238. Jørgensen, S. & Zaccour, G. (2007). Developments in differential game theory and numerical methods: economic and management applications. Computational Management Science, 4(2), 159-181.
239. Jorgenson, D. W. (1963). Capital theory and investment behaviour. The American Economic Review, 52 (2), 247-259.
240. Jorgenson, D. W. (1967). The theory of investment behaviour. In Ferber, R. (Ed.), Determinants of investment behavior (pp. 129-155). New York: Columbia University Press.
241. Jost, J. (2005). Postmodern analysis (3rd ed.). Berlin: Springer.
242. Kalish, S. (1983). Monopolist pricing with dynamic demand and production cost. Marketing Science, 2(2), 135-159.
243. Kamien, M. I. & Schwartz, N. L. (1971). Optimal maintenance and sale age for a machine subject to failure. Management Science, 17 (8), B498-B504.
244. Kamien, M. I. & Schwartz, N. L. (1991). Dynamic optimization: The calculus of variations and optimal control in economics and management (2nd ed.). Amsterdam: North-Holland.
245. Kandel, D. B. (2002). Stages and pathways of drug involvement: Examining the gateway hypothesis. New York: Cambridge University Press.
246. Kaplan, E. H., Mintz, A., Mishal, S., & Samban, C. (2005). What happened to suicide bombings in Israel? Insights from a terror stock model. Studies in Conflict and Terrorism, 28 (3), 225-235.
247. Karatzas, I. & Shreve, S. E. (1998). Methods of mathematical finance. New York: Springer.
248. Kaskosz, B. & Lojasiewicz, S. (1985). A maximum principle for generalized control systems. Nonlinear analysis: Theory, methods and applications, 9(2), 109-130.
249. Kaya, C. Y., Lucas, S. K., & Simakov, S. T. (2004). Computations for bang- bang constrained optimal control using a mathematical programming formulation. Optimal Control Applications and Methods, 25 (6), 295-308.
250. Kaya, C. Y. & Noakes, J. L. (1996). Computations and time-optimal controls. Optimal Control Applications and Methods, 1, 17 (3), 171-185.
251. Kaya, C. Y. & Noakes, J. L. (2003). Computational algorithm for timeoptimal switching control. Journal of Optimization Theory and Applications, 117 (1), 69-92.
252. Kelley, A. (1967). The stable, center-stable, center, center-unstable, unstable manifolds. Journal of Differential Equations, 3(4), 546-570.
253. Kelley, H. J., Kopp, R. E., & Moyer, H. G. (1967). Singular extremals. In Leitmann, G. (Ed.), Topics of optimization (pp. 63-101). New York: Academic.
254. Keohane, N. O. & Zeckhauser, R. J. (2003). The ecology of terror defense. Journal of Risk and Uncertainty, 26 (2-3), 201-29 .
255. Keyfitz, B. L. & Keyfitz, N. (1997). The McKendrick partial differential equation and its uses in epidemiology and population study. Mathematical and Computer Modelling, 26 (6), 1-9.
256. Keyfitz, N. (1977). Applied mathematical demography. New York: Wiley.
257. Kierzenka, J. & Shampine, L. F. (2001). A BVP solver based on residual control and the maltab pse. ACM Transactions on Mathematical Software (TOMS), 27 (3), 299-316.
258. Kiseleva, T. & Wagener, F. O. O. (2008). The dependence of indifference regions on the discount rate. Preprint.
259. Kleiman, M. A. R. (1988). Crackdowns: The effects of intensive enforcement on retail heroin dealing. In Chaiken, M. (Ed.), Street Level Drug Enforcement: Examining the Issues (pp. 3-34). Washington, DC: National Institute of Justice.
260. Kleiman, M. A. R. (1993). Enforcement swamping: A positive-feedback mechanism in rates of illicit activity. Mathematical and Computer Modelling, 17 (2), 65-75.
261. Kolmanovskii, V. B. & Shaikhet, L. E. (1996). Control of systems with aftereffect. Rhode Island: American Mathematical Society.
262. Koopmans, T. C. (1965). On the concept of optimal economic growth. Pontificiae Academiae Scientiarum Scripta Varia, 28 (1), 225-300.
263. Kraft, D. (1994). TOMP-Fortran modules for optimal control calculations. ACM Transactions on Mathematical Software, 20 (3), 262-281.
264. Krauskopf, B., Osinga, H. M., & Galan-Vioque, J. (Eds.). (2007). Numerical continuation methods for dynamical systems: path following and boundary value problems. Dordrecht: Springer.
265. Krugman, P. (1991). History versus expectations. The Quarterly Journal of Economics, 106 (2), 651-67.
266. Kuhn, M., Prskawetz, A., Wrzaczek, S., & Feichtinger, G. (2007). Health, survival, and consumption over the life cycle: An optimal control approach. Working paper.
267. Kunkel, P. & von dem Hagen, O. (2000). Numerical solution of infinite-horizon optimal-control problems. Computational Economics, 16 (3), 189-205.
268. Kurz, M. (1968). The general instability of a class of competitive growth processes. Review of Economic Studies, 35 (2), 155-174.
269. Kurzhanski, A. B. (2007). 50 years of coexistence in control: The contributions of the Russian community. European Journal of Control, 13 (1), 49-60.
270. Kuznetsov, Y. A. (1998). Elements of applied bifurcation theory (2nd ed.). New York: Springer.
271. Lawden, D. F. (1964). Optimal trajectories for space navigation. The Mathematical Gazette, 48 (366), 478-479.
272. Lehner, M., Meran, G., & Moller, J. (1980). De Statu Corruptionis. Entscheidungslogische Ein̈ubungen in die ḧohere Amoraliẗat. Konstanz: Faude.
273. Leitmann, G. (1974). Cooperative and non-cooperative many players differential Games. New York: Springer.
274. Lempio, F. & Veliov, V. M. (1998). Discrete approximations of differential inclusions. GAMM Mitteilungen der Gesellschaft f̈ur Angewandte Mathematik und Mechanik, 21 (2), 103-135.
275. Leonard, D. (1981). The signs of the costate variables and the sufficiency conditions in a class of optimal control problems. Economics Letters, 8(4), 321-325.
276. Leonard, D. & Long, N. V. (1992). Optimal control theory and static optimization in economics. Cambridge: Cambridge University Press.
277. Levin, G., Roberts, E. B., & Hirsch, G. B. (1975). The persistent poppy: A computer-aided search for heroin Policy. Cambridge, MA: Ballinger Publishing Company.
278. Levy, D. T., Chaloupka, F., Gitchell, J., Mendez, D., & Warner, K. E. (2002). The use of simulation models for the surveillance, justification and understanding of tobacco control policies. Health Care Management Science, 5(2), 113-120.
279. Lewis, R. M. (1980). Definitions of order and junction conditions in singular optimal control problems. SIAM Journal on Control and Optimization, 18 (1), 21-32.
280. 2market. Journal of Environmental Economics and Management, 41 (3), 295-311.
281. Liviatan, N. & Samuelson, P. A. (1969). Notes on turnpikes: Stable and unstable. Journal of Economic Theory, 1, 454-475.
282. Loewen, P. D. (1993). Optimal control via nonsmooth analysis, volume 2 of CRM Proceedings & Lecture Notes. Providence, RI: AmericanMathematical Society.
283. Long, N. V. & Shimomura, K. (2003). A new proof of the maximum principle. Economic Theory, 22 (3), 671-674.
284. Lorenz, E. N. (1963). Deterministic nonperiodic flow. Journal of the Atmospheric Sciences, 20 (2), 130-141.
285. Lorenz, H. W. (1993). Nonlinear dynamical economics and chaotic motion (2nd ed.). Berlin: Springer.
286. Lucas, R. E. (1988). On the mechanics of economic development. Journal of Monetary Economics, 22 (1), 3-42.
287. Ludwig, T. (1978). Optimale Expansionspfade der Unternehmung.Wiesbaden: Gabler.
288. Luenberger, D. G. (1997). Investment science. New York: Oxford University Press.
289. MacCoun, R. (1998). Toward a psychology of harm reduction. American Psychologist, 53 (11), 1199-1208.
290. MacCoun, R., Reuter, P., & Schelling, T. (1996). Assessing alternative drug control regimes. Journal of Policy Analysis and Management, 15 (3), 330- 352.
291. MacDonald, N. (1989). Biological delay systems: Linear stability theory. Cambridge: Cambridge University Press.
292. Magill, M. J. (1970). On a general economic theory of motion. New York: Springer.
293. Majumdar, M., Mitra, T., & Nishimura, K. (2000). Optimization and chaos. Berlin: Springer.
294. Makris, M. (2001). Necessary conditions for infinite-horizon discounted twostage optimal control problems. Journal of Economic Dynamics and Control, 25 (12), 1935-1950.
295. Malanowski, K., Maurer, H., & Pickenhain, S. (2004). Second order sufficient optimality conditions for state constrained optimal control problems. Journal of Optimization Theory and Applications, 123 (3), 594-617.
296. Maler, K. G., Xepapadeas, A., & de Zeeuw, A. (2003). The economics of shallow lakes. Environmental and Resource Economics, 26 (4), 603-624.
297. Mangasarian, O. L. & Fromovitz, S. (1967). The Fritz John necessary conditions in the presence of equality and inequality constraints. Journal of Mathematical Analysis and Applications, 17, 37-47.
298. Marsden, J. & McCracken, M. (1976). Hopf bifurcation and its applications. New York: Springer.
299. Maurer, H., Buskens, C., Kim, J. H., & Kaya, C. Y. (2005). Optimization methods for the verification of second-order sufficient conditions for bangbang controls. Optimal Control Methods and Applications, 26 (3), 129-156.
300. Maurer, H. & Oberle, H. J. (2002). Second order sufficient conditions for optimal control problems with free final time: The Riccati approach. SIAM Journal for Control and Optimization, 41 (2), 380-403.
301. Maurer, H. & Pickenhain, S. (1995). Second-order sufficient conditions for control problems with mixed control-state constraints. Journal of Optimization Theory and Applications, 86 (3), 649-667.
302. Mautner, K. (2002). A dynamic one-state two-control optimization model of the current australian heroin problem. Master's thesis, Vienna University of Technology.
303. Mayne, D. Q. (2007). Personal impressions of the dawn of modern control. European Journal of Control, 13 (1), 61-70.
304. McIntyre, J. & Paiewonsky, B. (1967). On optimal control with bounded state variables. In C. T. Leondes (Ed.), Advances in Control Systems, volume 5 (pp. 389-419). New York: Academic.
305. McKendrick, A. G. (1926). Applications of mathematics to medical problems. Proceedings of the Edinburgh Mathematical Society, 44, 98-130.
306. McKenzie, L. W. (1986). Optimal economic growth, turnpike theorems and comparative dynamics. In Handbook of Mathematical Economics, volume III (pp. 1281-1355). Amsterdam: North-Holland.
307. McShane, E. J. (1939). On multipliers for Lagrange problems. American Journal of Mathematics, 61 (4), 809-819.
308. Mehlmann, A. (1988). Applied differential games. New York: Plenum.
309. Mendez, D. & Warner, K. E. (2000). Smoking prevalence in 2010: Why the healthy people goal is unattainable. American Journal of Public Health, 90 (3), 401-403.
310. Mendez, D., Warner, K. E., & Courant, P. N. (1998). Has smoking cessation ceased? Expected trends in the prevalence of smoking in the United States. American Journal of Epidemiology, 148 (3), 249-258.
311. Mercenier, J. & Philippe, M. (2001). Temporal aggregation in a multi-sector economy with endogenous growth. Journal of Economic Dynamics and Control, 25 (8), 1179-1191.
312. Michel, P. (1982). On the transversality condition in infinite horizon optimal problems. Econometrica, 50 (4), 975-985.
313. Michel, V. (1996). Singular optimal control - The state of the art. AGTMReport 169, Laboratory of Technomathematics, Geomathematics Group, Department of Mathematics, University of Kaiserslautern.
314. Miele, A. (1962). Extremization of linear integrals by Green's theorem. In Leitmann, G. (Ed.), Optimization technics with applications to aerospace systems (pp. 68-98). New York: Academic.
315. Miller, B. & Rubinovich, E. (2003). Impulsive control in continuous and discrete-continuous systems. New York: Kluwer Academic.
316. Moore, M. H. (1973). Policies to achieve discrimination on the effective price of heroin. The American Economic Review, 63 (2), 270-277.
317. Morawetz, J. (2003). Sensitivity analysis in an optimal control model of the australian heroin epidemic. Master's thesis, Vienna University of Technology.
318. Moyzisch, F. (2003). Sensitivity analysis in a one-state three-control model of the u.s. cocaine epidemic. Master's thesis, Vienna University of Technology.
319. Muller, J. (1999). Optimal vaccination patterns in age-structured populations. SIAM Journal on Applied Mathematics, 59 (1), 222-241.
320. Musto, D. F. (1987). The American disease: Origins of narcotic control. New York: Oxford University Press.
321. Muzicant, J. (1980). Systeme mit verteilten Parametern in der Biöokonomie: Ein Maximumprinzip zur Kontrolle altersstrukturierter Modelle. PhD thesis, Vienna University of Technology.
322. Näslund, B. (1966). A model of capital budgeting under risk. Journal of Business, 39 (2), 257-271.
323. Näslund, B. (1969). Optimal rotation and thinning. Forest Science, 15 (4), 446-451.
324. Nerlove, M. & Arrow, K. J. (1962). Optimal advertising policy under dynamic conditions. Economica, 29 (114), 129-142.
325. Neustadt, L. W. (1976). Optimization: A theory of necessary conditions. Princeton University Press.
326. Nishimura, K. & Sorger, G. (1996). Optimal cycles and chaos: A survey. Studies in Nonlinear Dynamics and Econometrics, 1(1), 11-28.
327. Oberle, H. J. (1986). Numerical solution of minimax optimal control problems by multiple shooting technique. Journal of Optimization Theory and Applications, 50 (2), 331-357.
328. Oberle, H. J. (2006). Variationsrechnung und Optimale Steuerung. Lecture Notes, University of Hamburg, Department of Mathematics. http://www.math.uni- hamburg.de/home/oberle/skripte/varopt.html.
329. Office of National Drug Control Policy (1996). The National Drug Control Strategy: 1996. TheWhite House.
330. Orphanides, A. & Zervos, V. (1998). Myopia and addictive behaviour. The Economic Journal, 108 (446), 75-91.
331. Ozdenoren, E., Salant, S., & Silverman, D. (2006).Willpower and the optimal control of visceral urges. NBER Working Paper 12278, National Bureau of Economic Research.
332. Pampel, T. (2000). Numerical approximation of generalized connecting orbits.PhD thesis, University of Bielefeld.
333. Penot, J.-P. (1997). Multipliers and generalized derivatives of performance functions. Journal of Optimization Theory and Applications, 93 (3), 609- 618.
334. Penot, J.-P. (2004). Differentiability properties of optimal value functions. Canadian Journal of Mathematics, 56 (4), 825-842.
335. Pesch, H. J. & Bulirsch, R. (1994). The maximum principle, Bellman's equation, and Carath́eodory's work. Journal of Optimization Theory and Applications, 80 (2), 199-225.
336. Pollack, H. A. (2001). Cost-effectiveness of harm reduction in preventing hepatitis C among injection drug users. Medical Decision Making, 21 (5), 357- 365.
337. Pontryagin, L. S., Boltyanski, V. G., Gamkrelidze, R. V., & Mishchenko, E. F. (1962). The mathematical theory of optimal processes. New York: Wiley.
338. Pytlak, R. (1999). Numerical methods for optimal control problems with state constraints, volume 1707 of Lecture Notes in Mathematics. Berlin: Springer.
339. Ramsey, F. P. (1928). A mathematical theory of saving. Economic Journal, 38 (152), 543-559.
340. Ravn, H. F. (1999). Discrete time optimal control. PhD thesis, Technical University of Denmark.
341. Rinaldi, S., Feichtinger, G., & Wirl, F. (1998). Corruption dynamics in democratic systems. Complexity, 3(5), 53-64.
342. Robbins, H. (1967). A generalized Legendre-Clebsch condition for the singular cases of optimal control. IBM Journal of Research and Development, 11 (2), 361-372.
343. Rockafellar, R. (1970). Convex analysis. Princeton, NJ: Princeton University Press.
344. Romer, P. (1990). Endogenous technological change. Journal of Political Economy, 98 (5), 71-102.
345. Rose-Ackerman, S. (1978). Corruption: A study in political economy. New York: Academic.
346. Rosen, S. (1988). The value of changes in live expectancy. Journal of Risk and Uncertainty, 1(3), 285-304.
347. Rosenzweig, M. L. & MacArthur, R. H. (1963). Graphical representation and stability conditions of predator-prey interactions. The American Naturalist, 162 (895), 209-223.
348. Rossi, C. (1999). Estimating the prevalence of injecting drug users on the basis of Markov models of the HIV/AIDS epidemic: Applications to Italian data. Health Care Management Science, 2(3), 173-179.
349. Rossi, C. (2001). A mover-stayer type model for epidemics of problematic drug use. Bulletin on Narcotics, 53 (1-2), 39-64.
350. Rudel, S. (2006). Optimal dynamic harm reduction in models of illicit drug consumption. Master's thesis, Vienna University of Technology.
351. Rydell, C. P., Caulkins, J. P., & Everingham, S. S. (1996). Enforcement or treatment? Modeling the relative efficacy of alternatives for controlling cocaine. Operations Research, 44 (5), 687-695.
352. Rydell, C. P. & Everingham, S. S. (1994). Controlling cocaine: Supply versus demand programs. MR-331-ONDCP/A/DPRC. Santa Monica, CA: RAND.
353. Ryder, H. E. & Heal, G. M. (1973). Optimal growth with intertemporally dependent preferences. Review of Economic Studies, 40, 1-33.
354. Sagan, H. (1969). Introduction to the calculus of variations. New-York: McGraw-Hill Book Company.
355. Saglam, H. C. (2002). Optimal pattern of technology adoption under embodiment with a finite planning horizon: A multi-stage optimal control approach. Discussion Paper 2002031, Universit́e Catholique de Louvain, Institut de Recherches Economiques et Sociales (IRES).
356. Schelling, T. (1967). Economic analysis of organized crime. In President's Comission on Law Enforcement and the Administration of Justice Task Force. Washington, DC: Government Printing Office.
357. Schelling, T. (1971). Dynamic models of segregation. Journal of Mathematical Sociology, 1(2), 143-186.
358. Schelling, T. (1973). Hockey helmets, concealed weapons, and daylight saving: A study of binary choices with externalities. Journal of Conflict Resolution, 17 (3), 381-428.
359. Schwartz, L. (1950). Theorie des distributions. Paris: Hermann and Cie.
360. Seidl, A. (2008). Optimal control of a two-state diffusion model. PhD thesis, Vienna University of Technology.
361. Seierstad, A. & Sydsaeter, K. (1977). Sufficient conditions in optimal control theory. International Economic Review, 18 (2), 367-391.
362. Seierstad, A. & Sydsaeter, K. (1986). Optimal control theory with economic applications. Amsterdam: North-Holland.
363. Sethi, S. P. (1974). Sufficient conditions for the optimal control of a class of systems with continuous lags. Journal of Optimization Theory and Applications, 13 (5), 545-552.
364. Sethi, S. P. (1977). Nearest feasible paths in optimal control problems: Theory, examples, and counterexamples. Journal of Optimization Theory and Applications, 23 (4), 563-579.
365. Sethi, S. P. (1978). A survey of management science applications of the deterministic maximum principle. TIMS Studies in the Management Science, 9, 33-68.
366. Sethi, S. P. (1979a). Optimal advertising policy with the contagion model. Journal of Optimization Theory and Applications, 29 (4), 615-627.
367. Sethi, S. P. (1979b). Optimal pilfering policies for dynamic continuous thieves. Management Science, 25 (6), 535-542.
368. Sethi, S. P. (1983). Deterministic and stochastic optimization of a dynamic advertising model. Optimal Control Applications and Methods, 4(2), 179- 184.
369. Sethi, S. P. (1997). Optimal consumption and investment with bankruptcy. Norwell, MA: Kluwer Academic.
370. Sethi, S. P. & Thompson, G. L. (2000). Optimal control theory applications to management science and economics (2nd ed.). Boston: Kluwer Academic.
371. Sethi, S. P. & Zhang, Q. (1994). Hierarchical decision making in stochastic manufacturing systems. Systems and Control: Foundations and Applications. Boston, Cambridge, MA: Birkhauser.
372. Seydel, R. (1994). Practical bifurcation and stability analysis: From equilibrium to chaos (2nd ed.). New York: Springer.
373. Shell, K. (1967). Optimal program of capital accumulation for an economy in which there is exogenous technical change. In K. Shell (Ed.), Essays on the Theory of Optimal Economic Growth (pp. 1-30). Cambridge: MIT.
374. Shell, K. (1969). Application of Pontryagin'smaximum principle to economics. In H. W. Kuhn & G. P. Szegö (Eds.), Mathematical Systems Theory and Economics, volume 1. Berlin: Springer.
375. Shleifer, A. & Vishny, R. W. (1993). Corruption. Quarterly Journal of Economics, 108 (3), 599-617.
376. Shub, M. (1987). Global stability of dynamical systems. New York: Springer.
377. Shvartsman, I. A. (2007). New approximation method in the proof of the maximum principle for nonsmooth optimal control problems with state constraints. Journal of Mathematical Analysis and Applications, 326 (2), 974-1000.
378. Skiba, A. K. (1978). Optimal growth with a convex-concave production function. Econometrica, 46 (3), 527-539.
379. Smith, D. R. (1974). Variational methods in optimization. Englewood Cliffs, NJ: Prentice-Hall.
380. Solow, R. (1956). Technical change and the aggregate production function. Review of Economics and Statistics, 33 (3), 127-159.
381. Sparrow, C. (1982). The Lorenz equations: Bifurcations, chaos, and strange attractors. New York: Springer.
382. Stern, L. E. (1984). Criteria of optimality in the infinite-time optimal control problem. Journal of Optimization Theory and Applications, 44 (3), 497-508.
383. Strogatz, S. H. (1994). Nonlinear dynamics and chaos. Massachusetts: Addison-Wesley.
384. Sussmann, H. J. & Willems, J. C. (1997). 300 years of optimal control: From the brachystochrone to the maximum principle. Control Systems Magazine, IEEE, 17 (3), 32-44.
385. Sussmann, H. J. & Willems, J. C. (2002). The brachistochrone problem and modern control theory. In A. Anzaldo-Meneses, B. Bonnard, J. P. Gauthier, & F. Monroy-Perez (Eds.), Contemporary Trends in Non-Linear Geometric Control Theory and its Applications (pp. 113-165). Singapore: World Scientific.
386. Swan, G. W. (1988). General applications of optimal control theory in cancer chemotherapy. Mathematical Medicine and Biology, 5(4), 303-316.
387. Swaton, N. (2005). Optimal dynamic allocation of prevention, treatment and law enforcement in a one-state model of the u.s. cocaine epidemic. Master's thesis, Vienna University of Technology.
388. Tengs, T. O., Ahmad, S., Moore, R., & Gage, E. (2004). Federal policy mandating safer cigarettes: A hypothetical simulation of the anticipated population health gains or losses. Journal of Policy Analysis and Management, 23 (4), 857-872.
389. Tengs, T. O., Osgood, N. D., & Chen, L. L. (2001). The cost-effectiveness of intensive national school-based anti-tobacco education: Results from the tobacco policy model. Preventive Medicine, 33 (6), 558-570.
390. Thompson, G. L. (1968). Optimal maintenance policy and sale date of a machine. Management Science, 14 (9), 543-550.
391. Tomiyama, K. (1985). Two-stage optimal control problems and optimality conditions. Journal of Economic Dynamics and Control, 9(3), 317-337.
392. Tomiyama, K. & Rossana, R. J. (1989). Two-stage optimal control problems with an explicit switch point dependence: Optimality criteria and an example of delivery lags and investment. Journal of Economic Dynamics and Control, 13 (3), 319-337.
393. Tonelli, L. (1915). Sur une ḿethode directe du calcul des variations. Rendiconti del Circolo Matematico di Palermo, 39, 233-264.
394. Tragler, G. (1998). Optimal control of illicit drug consumption: Treatment versus enforcement. PhD thesis, Vienna University of Technology.
395. Tragler, G., Caulkins, J. P., & Feichtinger, G. (2001). Optimal dynamic allocation of treatment and enforcement in illicit drug control. Operations Research, 49 (3), 352-362.
396. Troger, H. & Steindl, A. (1991). Nonlinear stability and bifurcation theory. Vienna: Springer.
397. Tsutsui, S. & Mino, K. (1990). Non-linear strategies in dynamic competition with sticky prices. Journal of Economic Theory, 52 (1), 136-161.
398. Tu, P. N. V. (1991). Introductory optimization dynamics (2nd ed.). Berlin: Springer.
399. Udwadia, F., Leitmann, G., & Lambertini, L. (2006). A dynamical model of terrorism. Discrete Dynamics in Nature and Society, 2006, 1-32.
400. Ushiki, S. (1980). Analytic expressions of unstable manifolds. Proceedings of the Japan Academy (Series A), 56 (6), 239-244.
401. Valentine, F. A. (1937). The problem of Lagrange with differential inequalities as added side conditions. In Contributions of the Theory of the Calculus of Variations. Chicago: University of Chicago Press.
402. van Hilten, O., Kort, P. M., & van Loon, P. J. (1993). Dynamic policies of the firm - An optimal control approach. Berlin: Springer.
403. van Loon, P. J. (1985). Investment grants and alternatives to stimulate industry and employment. In Feichtinger, G. (Ed.), Optimal control theory and economic analysis (pp. 331-340). Amsterdam: North-Holland.
404. Verheyen, P. A. (1992). The jump in models with irreversible investments. In Feichtinger, G. (Ed.), Dynamic Economic Models and Optimal Control, volume 4 (pp. 75-89). Amsterdam: Elsevier Science.
405. Verhulst, P. F. (1838). Notice sur la loi que la population suit dans son accroissement. Correspondance math́ematique et physique, 10, 113-121 .
406. Vinter, R. B. (2000). Optimal control. Boston: Birkḧauser.
407. von Stryk, O. & Bulirsch, R. (1992). Direct and indirect methods for trajectory optimization. Annals of Operations Research, 37 (1), 357-373.
408. Wagener, F. O. O. (2003). Skiba points and heteroclinic bifurcations, with applications to the shallow lake system. Journal of Economic Dynamics and Control, 27 (9), 1533-1561.
409. Wagener, F. O. O. (2006). Skiba points for small discount rates. Journal of Optimization Theory and Applications, 128 (2), 261-277.
410. Wallner, D. (2005). Optimal control of the U. S. cocaine epidemic: Traditional approach vs. harm reduction. Master's thesis, Vienna University of Technology.
411. Webb, G. F. (1985). Theory of nonlinear age-dependent population dynamics. New York: Dekker.
412. Weiser, M. & Deuflhard, P. (2007). Inexact central path following algorithms for optimal control problems. SIAM Journal on Control and Optimization, 46 (3), 792-815.
413. Wiggins, S. (1990). Introduction to applied nonlinear dynamical systems and chaos. New York: Springer.
414. Willems, J. C. (2007). In control, almost from the beginning until the day after tomorrow. European Journal of Control, 13 (1), 71-81.
415. Wirl, F. (1992). Cyclical strategies in two-dimensional optimal control models: Necessary conditions and existence. Annals of Operations Research, 37 (1), 345-356.
416. Wirl, F. (1999). Complex dynamic environmental policies. Resource and Energy Economics, 21 (1), 19-41.
417. Wirl, F. & Feichtinger, G. (2005). History dependence in concave economies. Journal of Economic Behavior and Organization, 57 (4), 390-407.
418. Wirl, F., Novak, A. J., Feichtinger, G., & Dawid, H. (1997). Indeterminacy of open-loop Nash equilibria: The ruling class versus the tabloid press. In H. G. Natke & Y. Ben-Haim (Eds.), Uncertainty: Models and Measures (pp. 124-136). Berlin: Akademie.
419. Wrzaczek, S., Kuhn, M., & Oeppen, J. (2007). Reproductive value as a factor in the value of life and the shadow price of of a member of the population. In submission.
420. Xue, A., Teo, K., Lu, Q., & Mei, S. (2006). Polynomial approximations for the stable and unstable manifolds of the hyperbolic equilibrium points using semi-tensor product. International Journal of Innovative Computing, Information and Control, 2(3), 593-608.
421. Yaari, M. E. (1965). Uncertain lifetime, life insurance, and the theory of the consumer. The Review of Economic Studies, 32 (2), 137-150.
422. Yeung, D. W. K. & Petrosyan, L. A. (2006). Cooperative stochastic differential games. New York: Springer.
423. Yong, J. & Zhou, X. Y. (1999). Stochastic controls: Hamiltonian systems and HJB equations. New York: Springer .
424. Zeidan, V. (1984). First and second order sufficient conditions for optimal control and the calculus of variations. Applied Mathematics and Optimization, 11 (1), 209-226.
425. Zeidan, V. & Zezza, P. (1988). Necessary conditions for optimal
426. Zeiler, I. (2004). Prevention, treatment and law enforcement in an optimal control model of cocaine use in the USA. Master's thesis, Vienna University of Technology.
427. Zeiler, I. (2008). Epidemics with multiple equilibria and DNS Curves: Optimal control in dynamic models of HIV/AIDS and of illicit drug use. PhD thesis, Vienna University of Technology.