An ordinal optimization approach to optimal control problems

Automatica

Volumn 35, Issue 2, 1999, Pages 331-338

  Deng, Mei ^a,c,d,e   Ho, Yu Chi ^{b,d,f,g,h,i,j}  

^a AT AND T LABS RESEARCH   (United States)

^b HARVARD UNIVERSITY   (United States)

^c TSINGHUA UNIVERSITY   (China)

^d HARVARD UNIVERSITY   (United States)

^e LUCENT TECHNOLOGIES   (United States)

^f MASSACHUSETTS INSTITUTE OF TECHNOLOGY   (United States)

^g Dept of Eng and Appl Mathematics ^*  (United States)

^h UNIVERSITY OF TEXAS AT AUSTIN   (United States)

ⁱ IEEE

^j Network Dynamics Inc

more..

Author keywords

Artificial intelligence; Optimal control; Optimization; Search methods; Simulation; Stochastic systems

Indexed keywords

ARTIFICIAL INTELLIGENCE; FEEDBACK CONTROL; OPTIMIZATION; STOCHASTIC CONTROL SYSTEMS;

ORDINAL OPTIMIZATION; WITSENHAUSEN PROBLEM;

OPTIMAL CONTROL SYSTEMS;

EID: 0033076187     PISSN: 00051098     EISSN: None     Source Type: Journal    
DOI: 10.1016/s0005-1098(98)00155-1     Document Type: Article

References (19)

1. Baglietto, M., Parisini, T., & Zoppoli, R. (1997). Nonlinear approximations for the solution of team optimal control problems. Proc. 36th Conf. on Decision and Control (pp. 4592-4594).
2. Bansal, R., & Basar, T. (1987). Stochastic teams with nonclassical information revisited: when is an affine law optimal?. IEEE Trans. Automat. Control, 32(6), 554-559.
3. Dai, L. (1997). Convergence properties of ordinal comparison in the simulation of discrete event dynamic systems. JOTA, to appear.
4. Deng, M. (1995). Sampling-selection and space-narrowing methods for stochastic optimization. Ph.D. thesis, Harvard University, Harward.
5. Deng, M., Ho, Y.C., & Hu, J.Q. (1992). Effect of correlated estimation error in ordinal optimization. Proc. Winter Simulation Conf. (pp. 466-475).
6. Ganz, A., & Wang, X. (1994). Efficient algorithm for virtual topology design in multihop lightwave networks. IEEE/ACM Trans. Networking, 2.
7. Ho, Y.C. (1994), A new paradigm for stochastic optimization and parallel simulation. Proc. 1993 DES Workshop in IMA/U.Minn Lecture Notes Series. Springer, New York.
8. Ho, Y.C., & Deng, M. (1994). The problem of large search space in stochastic optimization. Proc. 33rd CDC (pp 1470-1475).
9. Ho, Y.C., & Larson, M. (1995). Ordinal optimization and rare event probability simulation. J. DEDS, 5(2-3).
10. Ho, Y.C., Sreenivas, R., & Vakili, P. (1992). Ordinal optimization of discrete event dynamic systems. J. DEDS, 2(2), 61-88.
11. Jang, C.S.R., Sun, C.T., & Mizutani, E. (1997). Neural-fuzzy and soft computing. Englewood Cliffs, NJ: Prentice-Hall.
12. Lau, T.W.E., & Ho, Y.C. (1997). Universal alignment probabilities and subset selection for ordinal optimization. JOTA, 39(3).
13. Lee, L.H., Yang, M.S., & Ho, Y.C. (1997). On stochastic optimization and its applications to manufacturing. Lecture Notes in Applied Mathematics Series, vol. 33 (pp 317-331).
14. Ruml, W., Ngo, J.T., Marks, J., & Sheiber, S. (1997). Easily search encoding for number partitioning. JOTA, to appear.
15. Papadimitriou, C.H., & Tsitsiklis, J.N. (1986). Intractable problems in control theory. SIAM J. Control Optim. 24(4), 639-654.
16. Patsis, N., Chen, C.H., & Larson, M. (1997). Parallel simulation of DEDS. IEEE Trans. Control Technol, to appear.
17. Wieseltheir, J.E., Barnhart, C.M., & Ephremides, A. (1995). Ordinal optimization of admission control in wireless multihop voice/data network via standard clock simulation. J. DEDS, 5(2-3).
18. Witsenhausen, H.S. (1968). A counterexample in stochastic optimum control. SIAM J. Control, 6(1).
19. Xie, X. (1997). Dynamics and convergence rate of ordinal comparison of stochastic discrete event systems. IEEE Trans. Automat. Control, to appear.