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In this paper, we consider the lot-sizing problem in a periodic-review inventory system under non-stationary stochastic demand. We propose a heuristic and compare its performance with the optimal solution given by dynamic programming for 90 problem instances. Across all the problem instances the heuristic averages 1.96% error, and is found to be at least 30 times faster than dynamic programming.
The research herein addresses the strategic capacity planning problem in a multi-product, multi-plant setting under demand uncertainty. Past research provides a number of useful insights on the relationship between the degree of flexibility and the optimal product-plant configuration, based on product demand, product price, and plant capacity. A few prior studies, however, have addressed both capacity...
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