Multi-objective Aggregate Production Planning for Multiple Products: A Local Search-Based Genetic Algorithm Optimization Approach

被引:0
作者
Lan-Fen Liu
Xin-Feng Yang
机构
[1] Lanzhou Jiaotong University,School of Traffic and Transportation Engineering
来源
International Journal of Computational Intelligence Systems | / 14卷
关键词
Aggregate production planning; Multi-product; Stabilities in the work force; Multi-objective; Genetic algorithm; Local search algorithm;
D O I
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中图分类号
学科分类号
摘要
The diversity of products and fierce competition make the stability and production cost of manufacturing industry more important. So, the purpose of this paper is to deal with the multi-product aggregate production planning (APP) problem considering stability in the workforce and total production costs, and propose an efficient algorithm. Taking into account the relationship of raw materials, inventory cost and product demand, a multi-objective programming model for multi-product APP problem is established to minimize total production costs and instability in the work force. To improve the efficiency of the algorithm, the feasible region of the planned production and the number of workers in each period are determined and a local search algorithm is used to improve the search ability. Based on the analysis of the feasible range, a genetic algorithm is designed to solve the model combined with the local search algorithm. For analyzing the effect of this algorithm, the information entropy strategy, NSGA-II strategy and multi-population strategy are compared and analyzed with examples, and the simulation results show that the model is feasible, and the NSGA-II algorithm based on the local search has a better performance in the multi-objective APP problem.
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