随机批量问题的两种新模型及其算法

Two New Models and the Algorithm for Stochastic Lot-sizing Problems

研究随机需求下 ,单层多产品、资源能力受限的批量问题 .对资源能力确定的情形 ,给出机会约束规划模型 .对资源能力不确定的情形 ,基于执行计划的策略提出了一种随机环境下的期望值模型 .本文采用基于随机模拟的遗传算法求解上述两种模型 .通过对算例结果进行方差分析 ,研究各种模型参数和环境变量对目标费用的影响 .最后 ,对该问题的进一步研究工作进行了展望 .

The single-stage, capacitated lot-sizing problems with multiple products and random demands are considered in this paper. A chance-constrained programming model and an expectation model under stochastic environment based on real production strategies are presented for the case of deterministic capacity constrained and the case of uncertain capacity respectively. The genetic algorithm based on stochastic simulation is used to solve both of the models. The paper studies the effects of various model parameters and environmental factors on the objective costs using analysis of variance, and concludes with some advice for future research activities in the end.