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Computing nonstationary (s, S) inventory policies via genetic algorithmKeywords: stochastic model applications , genetic algorithm , nonstationary inventory management Abstract: A periodic-review inventory model with nonstationary stochastic demand under an (s, S) policy is considered.We apply a genetic algorithm to solve for reorder points and order-up-to levels which minimize an expected total cost.A closed-form exact expression for the expected cost is obtained from a nonstationary discrete-time Markov chain. In ournumerical experiments, our approach performs very well.
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