摘要
建立了单机器生产和多车辆运输协同调度问题的数学模型,以最小化完工时间为优化目标。设计了改进的遗传算法,采取了染色体实数编码方式来表示订单的生产顺序,在解码过程中嵌入了局部优化算法来提高车辆路径的质量。经算例测试,相比现有文献中的一种遗传算法,改进的遗传算法使所有算例的解的平均质量提高了7.88%。
A mathematical model about the integrated single machine production ana mulupie vehicles transportation scheduling is first built and the objective is to minimize the makespan. Then, an adapted genetic algorithm is proposed with the chromosomes are coded by real number for representing the order production sequence,and a local search is embed in decoding of chromosomes to improve the vehicle routings. Moreover, the average solution quality of all generated instances is improved 7.88 % by the adapted genetic algorithm, compared with a genetic algorithm published in the literature.
出处
《工业工程与管理》
CSSCI
北大核心
2016年第2期86-91,共6页
Industrial Engineering and Management
基金
国家自然科学基金面上项目(71372133)
华中科技大学自主创新研究基金(2015QN174)
关键词
生产
车辆运输
调度
遗传算法
production
transportation
scheduling
genetic algorithm
