Markov decision process design : A framework for integrating strategic and operational decisions
We consider the problem of optimally designing a system for repeated use under uncertainty. We develop a modeling framework that integrates the design and operational phases, which are represented by a mixed-integer program and discounted-cost infinite-horizon Markov decision processes, respectively...
| Publié dans: | Operations research letters. - 1998. - 54(2024) vom: 25. Mai |
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| Auteur principal: | |
| Autres auteurs: | , |
| Format: | Article en ligne |
| Langue: | English |
| Publié: |
2024
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| Accès à la collection: | Operations research letters |
| Sujets: | Journal Article Bilevel optimization Design optimization Markov decision processes |
| Résumé: | We consider the problem of optimally designing a system for repeated use under uncertainty. We develop a modeling framework that integrates the design and operational phases, which are represented by a mixed-integer program and discounted-cost infinite-horizon Markov decision processes, respectively. We seek to simultaneously minimize the design costs and the subsequent expected operational costs. This problem setting arises naturally in several application areas, as we illustrate through examples. We derive a bilevel mixed-integer linear programming formulation for the problem and perform a computational study to demonstrate that realistic instances can be solved numerically |
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| Description: | Date Revised 02.05.2025 published: Print-Electronic Citation Status PubMed-not-MEDLINE |
| ISSN: | 1872-7468 |
| DOI: | 10.1016/j.orl.2024.107090 |