A GENETIC ALGORITHM BASED APPROACH FOR MULTI-PRODUCT LOT-SIZING AND SEQUENCING PROBLEM UNDER UNCERTAINTIES
The paper deals with multi-product lot-sizing and sequencing problem for a production line that treat intermediate items by lots. We consider the model with deterministic processing times. Two types of uncertainties were taken into account: random lead time (machine breakdowns) and random yield (rejects). In addition sequence dependent setup times are considered. Our study is focused on maximizing the probability of producing required quantity of items of each type to meet customers demand for a given finite planning horizon. A decomposition approach is proposed where sequencing and lot-sizing problems can be resolved separately one from another. For each sub-problem, we proposed a genetic algorithm with a local search. The computational results are compared with the results obtained for the same decomposition approach but using exact optimization procedures for the sub-problems.
Lot-sizing Sequencing Uncertainties.
K. Shchamialiova A. Dolgui F. Grimaud
Centre for Industrial Engineering and Computer Science Ecole des Mines de Saint Etienne 158, cours Fauriel, Saint Etienne, France
国际会议
上海
英文
1-6
2009-08-02（万方平台首次上网日期，不代表论文的发表时间）