计算机工程与应用 ›› 2011, Vol. 47 ›› Issue (17): 224-228.

• 工程与应用 • 上一篇    下一篇

求解敏捷供应链调度优化问题的混合遗传算法

王建华1,2,李 南2,郭 慧2   

  1. 1.江苏大学 工业工程系,江苏 镇江 212013
    2.南京航空航天大学 工业工程系,南京 210016
  • 收稿日期:1900-01-01 修回日期:1900-01-01 出版日期:2011-06-11 发布日期:2011-06-11

Hybrid genetic algorithm for agile supply chain scheduling optimization

WANG Jianhua1,2,LI Nan2,GUO Hui2   

  1. 1.Department of Industrial Engineering,Jiangsu University,Zhenjiang,Jiangsu 212013,China
    2.Department of Industrial Engineering,Nanjing University of Aeronautics and Astronautics,Nanjing 210016,China
  • Received:1900-01-01 Revised:1900-01-01 Online:2011-06-11 Published:2011-06-11

摘要: 针对敏捷供应链调度决策中,需求的时间、数量约束和供应商生产能力、可用调度时段约束造成系统优化的复杂性,设计结合贪婪算法的混合遗传算法进行求解。算法以供应链系统库存成本和运输成本为适应度函数,以包含企业信息、部件信息和调度时段信息的时段编码作为遗传编码,以线性次序交叉LOX算子和逆序变异INV算子进行交叉和变异操作,在解码过程中结合贪婪算法进行调度决策和适应度计算,保证算法在满足约束条件的基础上快速收敛到系统Pareto最优解,通过算例验证算法的有效性。

关键词: 敏捷供应链, 调度, 混合遗传算法, 贪婪算法, 优化

Abstract: The time and quantity constraints of each demand,the productivity and available scheduling periods of each supplier increase the complexity of Agile Supply Chain Scheduling(ASCS) problem.In order to resolve the ASCS optimization,this paper designs a Hybrid Genetic Algorithm(HGA) by combining common GA with greedy algorithm,which takes the sum cost of inventory and transportation of the supply chain as fitness function,period codes with the information of corp and its producing part and its available scheduling periods as genetic codes,linear order crossover and inversion mutation as crossover operator and mutation operator separately,and uses greedy algorithm to help decode and calculate fitness values to assure HGA that can achieve the problem’s Pareto optimal solution rapidly and steadily.Finally,a scheduling example verifies the practicality and effectiveness of the algorithm.

Key words: agile supply chain, scheduling, hybrid genetic algorithm, greedy algorithm, optimization