Optimization modelling: A practical approach

Optimization Modelling: A Practical Approach

Volumn , Issue , 2007, Pages 1-471

  Sarker, Ruhul A ^a   Newton, Charles S ^a,b  

^a UNIVERSITY OF NEW SOUTH WALES   (Australia)

^b DHURAKIJ PUNDIT UNIVERSITY   (Thailand)

Author keywords

[No Author keywords available]

Indexed keywords

EID: 85056418597     PISSN: None     EISSN: None     Source Type: Book    
DOI: None     Document Type: Book

References (157)

1. Bazaraa, M., Jarvis, J., and Sherali, H., Linear Programming and Network Flows, John Wiley & Sons, New York, 1990.
2. Freund, R. (contributed extensively), Professor George Dantzig: Linear programming founder turns 80, SIAM News, November 1994 (also available in http:==www.stanford.edu=group=SOL=dantzig.html).
3. Hillier, F. and Lieberman, G., Introduction to Operations Research, 8th ed., McGraw-Hill, Boston, 2005.
4. Taha, H.A., Operations Research: An Introduction, 4th ed., MacMillan Publishing Company, New York, 1989.
5. Turban, E. and Meredith, J., Fundamentals of Management Science, 6th ed., Irwin McGraw-Hill, Boston, MA, 1994.
6. Abdennadher, S. and Frühwirth, T., Essentials of Constraint Programming, Springer, Berlin, 2003.
7. Apt, K., Principles of Constraint Programming, Cambridge University Press, Cambridge, 2003.
8. Birge, J.R. and Louveaux, F., Introduction to Stochastic Programming, Springer, Berlin, 1997.
9. Castillo, E., Conejo, A.J., Pedregal, P., Garcia, R., and Alguacil, N., Building and Solving Mathematical Programming Models in Engineering and Science, John Wiley & Sons, Canada, 2002.
10. Glover, F. and Woolsey, E., Converting 0–1 polynomial programming problem to a 0–1 linear program, Operations Research, 22, 180, 1974.
11. Kall, P. and Mayer, J., Stochastic Linear Programming: Properties, Solution Methods, and Applications, Springer, 2006.
12. Kall, P. and Wallace, S.W., Stochastic Programming, John Wiley & Sons, New York, 1995.
13. Sarker, R. and Khan, L., Optimum batch size under periodic delivery policy, International Journal of Systems Science, 32, 1089, 2001.
14. Watters, L., Reduction of integer polynomial programming problems to zero–one linear programming problems, Operations Research, 15, 1171, 1967.
15. Ahuja, R., Magnanti, T., and Orlin, J., Network Flows: Theory, Algorithms and Applications, Prentice Hall, Englewood Cliffs, NJ, 1993.
16. Balakrishnan, J., Cheng, C.H., Conway, D.G., and Lau, C.M., A hybrid genetic algorithm for the dynamic plant layout problem, International Journal of Production Economics, 86, 107, 2003.
17. Baykasoglu, A. and Gindy, N.N.Z., A simulated annealing algorithm for dynamic layout problem, Computers and Operations Research, 28, 1403, 2001.
18. Bazaraa, M., Jarvis, J., and Sherali, H., Linear Programming and Network Flows, John Wiley & Sons, New York, 1990.
19. Castro, J. and Nabona, N., An implementation of linear and nonlinear multicommodity network flows, European Journal of Operational Research, 92, 37, 1996.
20. Chan, Y., DiSalvo, J.P., and Garrambone, M.W., A goal-seeking approach to capital budgeting, Socio-Economic Planning Sciences, 39, 165, 2005.
21. Chien, C. and Wu, W., A recursive computational procedure for container loading, Computers and Industrial Engineering, 35, 319, 1998.
22. Chien, C. and Wu, W., A framework of modularized heuristics for determining the container loading patterns, Computers and Industrial Engineering, 37, 339, 1999.
23. Correia, M., Oliveira, J., and Ferreira, J., Reel and sheet cutting at a paper mill, Computers and Operations Research, 31, 1223, 2004.
24. Degraeve, Z., Gochet, W., and Jans, R., Alternative formulations for a layout problem in the fashion industry, European Journal of Operational Research, 143, 80, 2002.
25. de Matta, R. and Miller, T., Production and inter-facility transportation scheduling for a process industry, European Journal of Operational Research, 158, 72, 2004.
26. Drezner, T., Location of multiple retail facilities with limited budget constraints—in continuous space, Journal of Retailing and Consumer Services, 5, 173, 1998.
27. Drezner, T., Drezner, Z., and Salhi, S., Solving the multiple competitive facilities
28. location problem, European Journal of Operational Research, 142, 38, 2002.
29. Eben-Chaime, M., Mehrez, A., and Markovich, G., Capacitated location–allocation problems on a line, Computers and Operations Research, 29, 459, 2002.
30. Elhedhli, S., Ranking lower bounds for the bin packing problem, European Journal of Operational Research, 160, 34, 2005.
31. Erkut, E. and Ingolfsson, A., Transport risk models for hazardous materials: Revisited, Operations Research Letters, 33, 81, 2005.
32. Gabrel, V., Knippel, A., and Minoux, M., Exact solution of multicommodity network optimization problems with general step cost functions, Operations Research Letters, 25, 15, 1999.
33. Georgiadis, M.C., Schilling, G., Rotstein, G.E., and Macchietto, S., A general mathematical programming approach for process plant layout, Computers and Chemical Engineering, 23, 823, 1999.
34. Gnoni, M.G., Iavagnilio, R., Mossa, G., Mummolo, G., and Di Leva, A., Production planning of a multi-site manufacturing system by hybrid modelling: A case study from the automotive industry, International Journal of Production Economics, 85, 251, 2003.
35. Göthe-Lundgren, M., Lundgren, J.T., and Persson, J.A., An optimization model for refinery production scheduling, International Journal of Production Economics, 78, 255, 2002.
36. Gue, K.R., A dynamic distribution model for combat logistics, Computers and Operations Research, 30, 367, 2003.
37. Hadjiat, M., Maurras, J., and Vaxes, Y., A primal partitioning approach for single and non-simultaneous multicommodity flow problems, European Journal of Operational Research, 123, 382, 2000.
38. Hall, N., Hershey, J., Dessler, L., and Stotts, R., (1992). A model for making project funding decisions at the national cancer institute, Operations Research, 40, 1040, 1992.
39. Jetlund, A.S. and Karimi, I.A., Improving the logistics of multi-compartment chemical tankers, Computers and Chemical Engineering, 28, 1267, 2004.
40. Johnston, R.E. and Sadinlija, E., A new model for complete solutions to one-dimensional cutting stock problems, European Journal of Operational Research, 153, 176, 2004.
41. Johnstone, D.P., Hill, R.R., and Moore, J.T., Mathematically Modelling munitions prepositioning and movement, Mathematical and Computer modelling, 39, 759, 2004.
42. Karimi, B., Fatemi Ghomi, S.M.T., and Wilson, J.M., The capacitated lot sizing problem: A review of models and algorithms, Omega, 31, 365, 2003.
43. Leighton, T., Makedon, F., Plotkin, S., Stein, C., Tardos, E., and Tragoudas, S., Fast approximation algorithms for multicommodity flow problems, Journal of Computer and System Sciences, 50, 228, 1995.
44. Lodi, A., Martello, S., and Monaci, M., Two dimensional packing problems: A survey, European Journal of Operational Research, 141, 241, 2002.
45. Mak, K.L., Wong, Y.S., and Chan, F.T.S., A genetic algorithm for facility layout problems, Computer Integrated Manufacturing Systems, 11, 113, 1998.
46. Malmborg, C.J. and Krishnakumar, B., Optimal storage assignment policies for multiaddress warehousing systems, IEEE Transactions on Systems, Man and Cybernetics, 19, 197, 1989.
47. Martello, E. and Toth, P., Knapsack Problems: Algorithms and Implementations, John Wiley & Sons, New York, 1990.
48. McGarvey, R.G. and Cavalier, T.M., Constrained location of competitive facilities in the plane, Computers and Operations Research, 32, 359, 2005.
49. Morabito, R. and Garcia, V., The cutting stock problem in a hardboard industry: A case study, Computers and Operations Research, 25, 469, 1998.
50. Ortíz-Gómez, A., Rico-Ramirez, V., and Hernández-Castro, S., Mixed-integer multiperiod model for the planning of oilfield production, Computers and Chemical Engineering, 26, 703, 2002.
51. Pattanamekar, P., Park, D., Rilett, L.R., Lee, J., and Lee, C., Dynamic and stochastic shortest path in transportation networks with two components of travel time uncertainty, Transportation Research Part C: Emerging Technologies, 11, 331, 2003.
52. Potts, C.N. and Whitehead, J.D., Workload balancing and loop layout in the design of a flexible manufacturing system, European Journal of Operational Research, 129, 326, 2001.
53. Rabinowitz, G. and Mehrez, A., A multi-echelon multi-commodity, logistic system design at the Dead Sea Works Ltd., Computers & Industrial Engineering, 39, 65, 2001.
54. ReVelle, C.S. and Eiselt, H.A., Location analysis: A synthesis and survey, European Journal of Operational Research, 165, 1, 2005.
55. Rönnqvist, M., A method for the cutting stock problem with different qualities, European Journal of Operational Research, 83, 57, 1995.
56. Schilling, G. and Georgiadis, M.C., An algorithm for the determination of optimal cutting patterns, Computers and Operations Research, 29, 1041, 2002.
57. Sung, K., Bell, M.G.H., Seong, M., and Park, S., Shortest paths in a network with time-dependent flow speeds, European Journal of Operational Research, 121, 32, 2000.
58. Tang, L., Liu, J., Rong, A., and Yang, Z., A multiple traveling salesman problem model for hot rolling scheduling in Shanghai Baoshan Iron & Steel Complex, European Journal of Operational Research, 124, 267, 2000.
59. Troncoso, J.J. and Garrido, R.A., Forestry production and logistics planning: An analysis using mixed-integer programming, Forest Policy and Economics, 7, 625, 2005.
60. Valerio de Carvalho, J.M., LP models for bin packing and cutting stock problems, European Journal of Operational Research, 141, 253, 2002.
61. Warsing, D.P., Souza, G.C., and Greis, N.P., Determining the value of dedicated multimodal cargo facilities in a multi-region distribution network, European Journal of Operational Research, 133, 81, 2001.
62. Weingartner, H.M., Mathematical Programming and the Analysis of Capital Budgeting Problems, Prentice-Hall, Englewood Cliffs, NJ, 1963.
63. Wolsey, L.A., MIP modelling of changeovers in production planning and scheduling problems, European Journal of Operational Research, 99, 154, 1997.
64. Wu, C-C. and Chang, N-B., Corporate optimal production planning with varying environmental costs: A grey compromise programming approach, European Journal of Operational Research, 155, 68, 2004.
65. Yan, H-S., Zhang, X-D., and Jiang, M., Hierarchical production planning with demand constraints, Computers and Industrial Engineering, 46, 533, 2004.
66. Amini, M.M. and Racer, M., A hybrid heuristic for the generalized assignment problem, European Journal of Operational Research, 87, 343–348, 1995.
67. Bailey, J., Alfares, H., and Lin, W.Y., Optimization and heuristic models to integrate project task and manpower scheduling, Computers and Industrial Engineering, 29, 473, 1995.
68. Bard, J.F., Binici, C., and deSilva, A.H., Staff scheduling at the United States Postal Service, Computers and Operations Research, 30, 745, 2003.
69. Bertel, S. and Billaut, J.-C., A genetic algorithm for an industrial multiprocessor flow shop scheduling problem with recirculation, European Journal of Operational Research, 159, 651, 2004.
70. Bish, E.K., A multiple-crane-constrained scheduling problem in a container terminal, European Journal of Operational Research, 144, 83, 2003.
71. Calvo, R.W. and Cordone, R., A heuristic approach to the overnight security service problem, Computers and Operations Research, 30, 1269, 2003.
72. Cheang, B., Li, H., Lim, A., and Rodrigues, B., Nurse rostering problems––a bibliographic survey, European Journal of Operational Research, 151, 447, 2003.
73. Claessens, M.T., van Dijk, N.M., and Zwaneveld, P.J., Cost optimal allocation of rail
74. passenger lines, European Journal of Operational Research, 110, 474, 1998.
75. Daniels, R.L., Rummel, J.L., and Schantz, R., A model for warehouse order picking, European Journal of Operational Research, 105, 1, 1998.
76. Daskalaki, S. and Birbas, T., Efficient solutions for a university timetabling problem through integer programming, European Journal of Operational Research, 160, 106, 2005.
77. Dawid, H., König, J., and Strauss, C., An enhanced rostering model for airline crews, Computers and Operations Research, 28, 671, 2001.
78. Desaulniers, G., Lavigne, J., and Soumis, F., Multi-depot vehicle scheduling problems with time windows and waiting costs, European Journal of Operational Research, 111, 479, 1998.
79. Dimopoulou, M. and Miliotis, P., Implementation of a university course and examination timetabling system, European Journal of Operational Research, 130, 202, 2001.
80. Ernst, A.T., Jiang, H., Krishnamoorthy, M., and Sier, D., Staff scheduling and rostering: A review of applications, methods and models, European Journal of Operational Research, 153, 3, 2004.
81. Fagerholt, K. and Christiansen, M., A travelling salesman problem with allocation, time window and precedence constraints—an application to ship scheduling, International Transactions in Operational Research, 7, 231, 2000.
82. Ghoseiri, K., Szidarovszky, F., and Asgharpour, M.J., A multi-objective train scheduling model and solution, Transportation Research Part B: Methodological, 38, 927, 2004.
83. Helvig, C.S., Robins, G., and Zelikovsky, A., The moving-target travelling salesman problem, Journal of Algorithms, 49, 153, 2003.
84. Higgins, A., Kozan, E., and Ferreira, L., Optimal scheduling of trains on a single line track, Transportation Research Part B: Methodological, 30, 147, 1996.
85. Huq, F., Cutright, K., and Martin, C., Employee scheduling and makespan minimization in a flow shop with multi-processor work stations: A case study, Omega, 32, 121, 2004.
86. Kim, J.-U. and Kim, Y.-D., A decomposition approach to a multi-period vehicle scheduling problem, Omega, 27, 421, 1999.
87. Laguna, M., Kelly, J.P., González-Velarde, J., and Glover, F., Tabu search for the multilevel generalized assignment problem, European Journal of Operational Research, 82, 176, 1995.
88. Liao, C.-J., Sun, C.-L., and You, W.-C., Flow-shop scheduling with flexible processors, Computers and Operations Research, 22, 297, 1995.
89. Mascis, A. and Pacciarelli, D., Job-shop scheduling with blocking and no-wait constraints, European Journal of Operational Research, 143, 498, 2002.
90. Mattfeld, D.C. and Kopfer, H., Terminal operations management in vehicle transhipment, Transportation Research Part A: Policy and Practice, 37, 435, 2003.
91. Pan, Y., An improved branch and bound algorithm for single machine scheduling with deadlines to minimize total weighted completion time, Operations Research Letters, 31, 492, 2003.
92. Ruiz, R., Maroto, C., and Alcaraz, J., A decision support system for a real vehicle routing problem, European Journal of Operational Research, 153, 593, 2004.
93. Ruland, K.S., A model for aeromedical routing and scheduling, International Transactions in Operational Research, 6, 57, 1999.
94. Teixeira, J., Antunes, A.P., and de Sousa, J.P., Recyclable waste collection planning–– a case study, European Journal of Operational Research, 158, 543, 2004.
95. Toth, P. and Vigo, D., Models, relaxations and exact approaches for the capacitated vehicle routing problem, Discrete Applied Mathematics, 123, 487, 2002.
96. Bitran, G.R., Haas, E.A., and Hax, A.C., Hierarchical production planning: A single stage system, Operations Research, 29, 717, 1981.
97. Dempster, M.A., Fisher, M.L., Jansen, L., Lageweg, B.J., Lenstra, J.K., and Rinnooy Kan, A.H.G., Analytical evaluation of hierarchical planning systems, Operations Research, 29, 707, 1981.
98. Graves, S.C., Using Lagrangian techniques to solve hierarchical production planning problems, Management Science, 28, 260, 1982.
99. Hax, A.C. and Candea, D., Production and Inventory Management, Prentice-Hall
100. Hax, A.C. and Meal, H.C., Hierarchical integration of production planning and scheduling. In Geisler M.A. (Ed.), Studies in Management Science, Vol. I, Logistics, North Holland-American Elsevier, New York, 1975, p. 53.
101. Leong, G.K., Oliff, M.D., and Markland, R.E., Improved hierarchical production planning, Journal of Operations Management, 8, 90, 1989.
102. Liberatore, M.J. and Miller, T., A hierarchical production planning system, Interfaces, 15, 1, 1985.
103. Lin, C.W. and Moddie, C.L., Hierarchical production planning for a modern steel manufacturing system, International Journal of Production Research, 27, 613, 1989.
104. Saad, G.H., Hierarchical production planning system: Extensions and modifications, Journal of Operational Research Society, 41, 609, 1990.
105. Sarker, R.A. (2003) Operations Research Applications in a Mining Company, dissertation. de Verlag in Internet, Berlin, Germany.
106. Sumichrast, R.T. and Rurch, E.E., Understanding hierarchical production planning and scheduling models, Industrial Management, 27, 6, 1985.
107. Tabucanon, M.T. and Sasiwong, B., Production planning and scheduling for an iron and steel production system, Applied Mathematical Modelling, 15, 164, 1991.
108. Tsubone, H. and Sugawara, M., A hierarchical production planning system in the motor industry, OMEGA: International Journal of Management Science, 15, 113, 1987.
109. Ahuja, R., Magnanti, T., and Orlin, J., Network Flows: Theory, Algorithms and Applications, Prentice Hall, Englewood Cliffs, NJ, 1993.
110. Bazaraa, M., Jarvis, J., and Sherali, H., Linear Programming and Network Flows, John Wiley & Sons, New York, 1990.
111. Bertsekas, D., Nonlinear Programming, Athens Scientific, Belmont, 1995.
112. Coello, C.A.C., A comprehensive survey of evolutionary-based multiobjective optimization techniques, Knowledge and Information Systems: An International Journal, 1, 269–308, 1999.
113. Coello, C.A.C., Van Veldhuizen, D.A., and Lamont, G.B., Evolutionary Algorithms for Solving Multi-Objective Problems, Kluwer Academic Publishers, New York, 2002.
114. Dorigo, M. and Sttzle, T. Ant Colony Optimization, The MIT Press, Cambridge, MA, 2004.
115. Eiselt, H.A., Pederzoli, G., and Sandblom, C.-L., Continuous Optimization Models, Walter deGruyter, Berlin, 1987.
116. Glover, F. and Laguna, M., Tabu Search, Kluwer Academic Publishers, London, 1997.
117. Hillier, F. and Lieberman, G., Introduction to Operations Research, 8th ed., McGraw-Hill, Boston, MA, 2005.
118. Illes, T. and Terlaky, T. Pivot versus interior point methods: Pros and cons, European Journal of Operational Research, 140, 170–190, 2002.
119. Martin, R.K., Large Scale Linear and Integer Optimization, Kluwer, Boston, MA, 1999.
120. Miettinen, K., Nonlinear Multiobjective Optimization, Kluwer’s International Series in OR=MS, Kluwer Academic Publishers, Boston, 1999.
121. Mitchell, M., An Introduction to Genetic Algorithms (Complex Adaptive Systems), MIT Press, Cambridge, MA, 1998.
122. Moscato, P. and Norman, M.G., A ‘memetic’ approach for the traveling salesman problem, implementation of a computational ecology for combinatorial optimization on message-passing systems, Parallel Computing and Transputer Applications, M. Valero, E. Onate, M. Jane, J.L. Larriba, and B. Suarez, Eds., IOS Press, Amsterdam, 1992, pp. 187–194.
123. Nemhauser, G. and Wolsey, L., Integer and Combinatorial Optimization, John Wiley & Sons, New York, 1999.
124. Papadimitriou, C. and Steiglitz, K., Combinatorial Optimization: Algorithms and Complexity, Dover Publications, New York, 1998.
125. Sakawa, M. and Kato, K., Genetic algorithms with double strings for 0–1 programming problems, European Journal of Operational Research, 144, 581–597, 2003.
126. Sarker, R., Kamruzzaman, J., and Newton, C., Evolutionary optimization (EvOpt): A brief review and analysis, International Journal of Computational Intelligence and Applications, 3, 311–330, 2003.
127. Sierksma, G., Linear and Integer Programming: Theory and Practice, Marcel Dekker, Inc., New York, 1996.
128. Turban, E. and Meredith, J., Fundamentals of Management Science, 6th ed., Irwin McGraw-Hill, Boston, MA, 1994.
129. Van Laarhoven, P.J.M. and Aarts, E.H.L., Simulated Annealing: Theory and Applications, Kluwer Academic Publishers, Dordrecht, 1987.
130. Fadlalla, A., An experimental investigation of the impact of aggregation on the performance of data mining with logistic regression, Information and Management, 42, 695–707, 2005.
131. Garrett, T.A., Aggregated versus disaggregated data in regression analysis: Implications for inference, Economics Letters, 81, 61–65, 2003.
132. Neuman, W.L., Social Research Methods: Qualitative and Quantitative Approaches, Allyn and Bacon, Boston, MA, 2003.
133. Turban, E. and Meredith, J., Fundamentals of Management Science, 6th ed., Irwin McGraw-Hill, Boston, MA, 1994.
134. Agha, S.R., Use of goal programming and integer programming for water quality management—a case study of Gaza Strip, European Journal of Operational Research, 174, 1991–1998, 2006.
135. Cantor, K.P., Drinking water and cancer, Cancer Causes Control, 8, 292–308, 1997.
136. Ioannou, G., Streamlining the supply chain of the Hellenic Sugar Industry, Journal of Food Engineering, 70, 323–332, 2005.
137. Mavrotas, G., Diakoulaki, D., and Papayannakis, L., An energy planning approach based on mixed 0–1 multiple objective linear programming, International Transactions in Operations Research, 6, 231–244, 1999.
138. Sarker, R., Operations Research Applications in a Mining Company, Dissertation.dePublishing, Germany, 2003.
139. Sarker, R.A. and Gunn, E.A., A simple SLP algorithm for solving a class of nonlinear programs, European Journal of Operational Research, 101, 140–154, 1997.
140. Sarker, R. and Quaddus, M., Modelling a nationwide crop planning problem using a multiple criteria decision making Tool, International Journal of Computers and Industrial Engineering, 42, 541–553, 2002.
141. Sarker, R., Talukder, S., and Haque, A., Determination of optimum crop-mix for crop cultivation in Bangladesh, Applied Mathematical Modelling, 21, 621–632, 1997.
142. World Health Organization, Guidelines for Drinking Water Quality, 2nd ed., Volume 2, Health criteria and other supporting information, WHO, Geneva, 1996.
143. WHO guidelines for drinking water quality (1993) http:==www.who.int=media centre=factsheets=fs210=en=index.html
144. Aaytollahi, S., Narimani, M., and Moshfeghian, M., Intermittent gas lift in Aghajari oil field, a mathematical study, Journal of Petroleum Science and Engineering, 42, 245, 2004.
145. Camponogara, E. and Nakashima, P., Solving a gas lift optimization problem using dynamic programming, European Journal of Operational Research, 174, 1220, 2006.
146. Glover, F. and Woolsey, E., Converting 0–1 polynomial programming problem to a 0–1 linear program, Operations Research, 22, 180, 1974.
147. Gue, K.R., A dynamic distribution model for combat logistics, Computers and Operations Research, 30, 367, 2003.
148. Khan, L. and Sarker, R., An optimal batch size for a JIT manufacturing system, Computers and Industrial Engineering, 42, 127, 2002.
149. Kosmidis, V., Perkins, J., and Pistikopoulos, E., A mixed integer optimization formulation for the well scheduling problem on petroleum fields, Computers and Chemical Engineering, 29, 1523, 2005.
150. Ray, T. and Sarker, R., Multiobjective evolutionary approach to the solution of gas lift optimization problems, IEEE Congress on Evolutionary Computation (CEC2006), Vancouver, BC, Canada, 10951, 2006.
151. Sarker, R. and Gunn, E., Coal bank scheduling using a mathematical programming model, Applied Mathematical Modelling, 18, 672, 1994.
152. Sarker, R. and Khan, L., An optimal batch size for a production system operating under a periodic delivery policy, Computers and Industrial Engineering, 37, 711, 1999.
153. Sarker, R. and Newton, C., Genetic algorithm for solving economic lot size scheduling problem, Computers and Industrial Engineering, 42, 189, 2002.
154. Begum, S., Determination of optimum generation mix for the power sector of Bangladesh, Unpublished M.Sc. Thesis, Industrial and Production Engineering, Bangladesh University of Engineering and technology, Dhaka, 2004.
155. Buitrago, S., Rodriguez, E., and Espin, D., Global optimization techniques in gas allocation for continuous flow gas lift systems, SPE Gas Technology Conference, Calgary, Canada, SPE35616, 375, 1996.
156. Sarker, R. and Haque, A., Industrial engineering (IE) techniques in production decision, Journal of the Institution of Engineers, Bangladesh, 13, 67, 1985.
157. Sarker, R., Talukder, S., and Haque, A., Determination of optimum crop-mix for crop cultivation in Bangladesh, Applied Mathematical Modelling, 21, 621, 1997.