A STATE AGGREGATION APPROACH TO MANUFACTURING SYSTEMS HAVING MACHINE STATES WITH WEAK AND STRONG-INTERACTIONS

• 成果类型: Article
• 署名作者: JIANG, J; SETHI, SP
• 刊物名称: OPERATIONS RESEARCH
• ISSN/ISSBN: 0030-364X
• DOI: 10.1287/opre.39.6.970
• 发表日期: 1991
• 页码: 970-978
• 关键词: Dynamic Programming; optimal control; stochastic; continuous time; probability; Markov processes; HIERARCHICAL CONTROL OF MARKOV PROCESS DRIVEN SYSTEMS; production scheduling; hierarchical planning; MANUFACTURING WITH UNRELIABLE MACHINES

摘要

A hierarchical approach to control a manufacturing system, subject to multiple machine states modeled by a Markov process with weak and strong interactions, is suggested. The idea is to aggregate strongly interacting or high transition probability states within a group of states and consider only the transition between these groups for the analysis of the system in the long run. We show that such an aggregation results in a problem of reduced size, whose solution can be modified in a simple way to obtain an asymptotically optimal feedback solution to the original problem. Also, an example is solved to illustrate the results developed in the paper,