Series Expansion Optimization
نویسندگان
چکیده
In this chapter we present an innovative approach to combine common results of Markov decision theory and series expansions for optimization. We call our algorithm the series expansion optimization algorithm. Our algorithm efficiently determines the optimal policy of continuous-time Markov decision processes exactly or alternatively up to an arbitrarily small precision. We prove its convergence and efficiency and afterwards apply our algorithm to the optimization of multi-storage single-item inventory systems. We supplement our analysis by deriving the deviation matrix of such systems. Numerical examples are presented to illustrate the efficiency of the proposed algorithm. 5.
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