论文信息 - Solving Lot-Sizing and Sequencing Integrated Optimization Problems in Mixed-Model Production Systems

Solving Lot-Sizing and Sequencing Integrated Optimization Problems in Mixed-Model Production Systems

This paper is concerned about the lot-sizing and sequencing integrated optimization problems in mixed-model production systems composed of one mixed-model assembly line and one fabrication flow line. The optimization objective is minimizing the total makespan cost in regular hour, the overtime makespan cost and the holding cost in the whole production system. The mathematic models are presented and an adaptive genetic algorithm is developed for solving this problem. A traditional genetic algorithm is also designed for testing the optimization performance of the adaptive genetic algorithm. Computational experiments are conducted and the optimization results are compared between the above two algorithms. The comparison results show that the adaptive genetic algorithm is a feasible and effective method for solving this problem.

Bing Gang Wang

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