Replacement process decomposition for discounted Markov renewal programming |
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| Authors: | P. J. Schweitzer U. Sumita K. Ohno |
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| Affiliation: | (1) William E. Simon Graduate School of Business Administration, University of Rochester, 14627 Rochester, NY, USA;(2) Department of Systems Engineering, Nagoya Institute of Technology, Nagoya, Japan |
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| Abstract: | An iterative decomposition method is presented for computing the values in an infinite-horizon discounted Markov renewal program (DMRP). The states are partitioned intoM groups, with each iteration involving disaggregation of one group at a time, with the otherM–1 groups being collapsed intoM–1 singletons using the replacement process method. Each disaggregation also looks like a DMRP and can be performed by policy-iteration, value-iteration or linear programming. Anticipated benefits from the method include reduced computer time and memory requirements, scale-invariance and greater robustness to the starting point. |
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