Previous |  Up |  Next

Article

Keywords:
monotone minimizer in an optimization problem; Markov control process; total discounted cost; average cost; monotone optimal policy
Summary:
Firstly, in this paper there is considered a certain class of possibly unbounded optimization problems on Euclidean spaces, for which conditions that permit to obtain monotone minimizers are given. Secondly, the theory developed in the first part of the paper is applied to Markov control processes (MCPs) on real spaces with possibly unbounded cost function, and with possibly noncompact control sets, considering both the discounted and the average cost as optimality criterion. In the context described, conditions to obtain monotone optimal policies are provided. For the conditions of MCPs presented in the article, several controlled models including, in particular, two inventory/production systems and the linear regulator problem are supplied.
References:
[1] Ash R. B.: Real Variables with Basic Metric Space Topology. IEEE Press, New York 1993 MR 1193687 | Zbl 0920.26002
[2] Cruz-Suárez D., Montes-de-Oca, R., Salem-Silva F.: Conditions for the uniqueness of optimal policies of discounted Markov decision processes. Math. Methods Oper. Res. 60 (2004), 415–436 MR 2106092 | Zbl 1104.90053
[3] Cruz-Suárez D., Montes-de-Oca, R., Salem-Silva F.: Pointwise approximations of discounted Markov decision processes to optimal policies. Internat. J. Pure Appl. Math. 28 (2006), 265–281 MR 2228009 | Zbl 1131.90068
[4] Fu M. C., Marcus S. I., Wang, I-J: Monotone optimal policies for a transient queueing staffing problem. Oper. Res. 48 (2000), 327–331
[5] Gallish E.: On monotone optimal policies in a queueing model of M/G/1 type with controllable service time distribution. Adv. in Appl. Probab. 11 (1979), 870–887 MR 0544200
[6] Hernández-Lerma O., Lasserre J. B.: Discrete-Time Markov Control Processes. Springer-Verlag, New York 1996 MR 1363487 | Zbl 0928.93002
[7] Heyman D. P., Sobel M. J.: Stochastic Models in Operations Research, Vol. II. Stochastic Optimization. McGraw-Hill, New York 1984 Zbl 1072.90001
[8] Hinderer K., Stieglitz M.: Increasing and Lipschitz continuous minimizers in one-dimensional linear-convex systems without constraints: The continuous and the discrete case. Math. Methods Oper. Res. 44 (1996), 189–204 MR 1409065 | Zbl 0860.90126
[9] Kalin D.: A note on ‘monotone optimal policies for Markov decision processes’. Math. Programming 15 (1978), 220–222 MR 0509965 | Zbl 0387.90106
[10] Mendelssohn R., Sobel M.: Capital accumulation and the optimization of renewable resource models. J. Econom. Theory 23 (1980), 243–260 Zbl 0472.90015
[11] Pittenger A. O.: Monotonicity in a Markov decision process. Math. Oper. Res. 13 (1988), 65–73 MR 0931486 | Zbl 0646.90088
[12] Porteus E. L.: Foundations of Stochastic Inventory Theory. Stanford University Press, Stanford, Calif. 2002
[13] Puterman M. L.: Markov Decision Processes: Discrete Stochastic Dynamic Programming. Wiley, New York 1994 MR 1270015 | Zbl 1184.90170
[14] Rieder U.: Measurable selection theorems for optimization problems. Manuscripta Math. 24 (1978), 115–131 MR 0493590 | Zbl 0385.28005
[15] Ross S. M.: Introduction to Stochastic Dynamic Programming. Academic Press, San Diego 1983 MR 0749232 | Zbl 0567.90065
[16] Serfozo R. F.: Monotone optimal policies for Markov decision processes. Math. Programming Stud. 6 (1976), 202–215 MR 0459646 | Zbl 0368.60080
[17] Stidham, Sh., Weber R. R.: Monotonic and insensitive optimal policies for control of queues with undiscounted costs. Oper. Res. 37 (1989), 611–625 MR 1006813 | Zbl 0674.90029
[18] Stromberg K. R.: An Introduction to Classical Real Analysis. Wadsworth International Group, Belmont 1981 MR 0604364 | Zbl 0454.26001
[19] Sundaram R. K.: A First Course in Optimization Theory. Cambridge University Press, Cambridge 1996 MR 1402910 | Zbl 0885.90106
[20] Topkis D. M.: Minimizing a submodular function on a lattice. Oper. Res. 26 (1978), 305–321 MR 0468177 | Zbl 0379.90089
[21] Topkis D. M.: Supermodularity and Complementarity. Princeton University Press, Princeton, N. J. 1988 MR 1614637
Partner of
EuDML logo