模糊需求环境下多工艺批量生产计划

基于模糊集理论与容差法思想，研究了具有模糊客户需求与多工艺约束的批量生产计划问题，采用遗传算法寻找优化的计划方案。在遗传算法中，提出了分级构造初始种群的策略，按问题的多约束特征对交叉算子与变异算子重新进行了定义，并对不同模糊参数和优化目标下的批量计划进行了定性和定量评估。结果表明，在一定的需求满意度下以最大化生产利润为优化目标，不仅制造商可以获得较为理想的生产利润值，而且客户的需求满意度也能克服设定约束而达到更高值。

Research on the Capacitated Lot Sizing Problem with Fuzzy Demands

The lot sizing problem with fuzzy customer demands and multi technological constraints was studied by taking advantage of the fuzzy set theory and the idea of tolerance. Genetic algorithm (GA) was employed to search an optimized production plan. In the genetic algorithm, the initial population is generated through the hierarchical structure to ensure better starting points. In addition, crossover and mutation operators are redefined to handle the population in a coordinate way. The effectiveness of the approach was illustrated through an example. The lot size plan under different fuzzy parameters and optimization objectives was evaluated qualitatively and quantitatively. The result shows that by maximizing the production profits as optimization objective not only the manufacturer can obtain more satisfied profits but also the membership grade for customer demands can reach to a higher value. This study provides a powerful means for decision makers to determine production plan under fuzzy business environment in a manufacturing enterprises.