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Experimental study of a decomposition approach for sequencing and lot-sizing under uncertainties

We consider a stochastic multi-product sequencing and lot-sizing problem. The two following types of uncertainties are taken into account: random lead time due to machine breakdowns and random yield because of rejects. It is assumed that there is a sequence dependent setup time between lots of different products. The goal is to maximize the probability of satisfying given demands for all products. A decomposition approach is used to separate sequencing and lot-sizing sub-problems. Previous works have focused on the lot-sizing part of this problem. A dynamic programming and a memetic algorithm were proposed. The objective of this new paper is to integrate an integer program for the sequencing sub-problem into this decomposition framework, and to evaluate the performance of the overall approach via computational tests.