摘要
在考虑产品需求速率的前提下,提出了调整加工成本的新方法,建立了混流装配线平衡问题的多目标优化模型。设计了基于自然数序列和拓扑排序的改进遗传算法对模型进行求解,改进交叉、变异操作来保护优秀基因,提出了种群扩张机制。对经典问题的计算试验结果表明,改进遗传算法在降低生产节拍的同时能优化产品加工成本,在求解效率和求解质量方面有显著的成效。
Under the consideration of product demand ratio, a new method to adjust the operating costs was pro- posed, and the multi-objective optimization model for mixed-model assembly line balancing problem was formulated. An improved genetic algorithm base on natural number code and topological sorting was designed to solve the model. The crossover and mutation operation of standard genetic algorithm was improved to protect excellent genes, and the population expansion mechanism was proposed. Through testing for benchmark problems, the -results showed that the proposed algorithm could decrease the cycle time and optimize product processing costs, and the improved genetic algorithm also had a significant effect in decrease computing time.
出处
《计算机集成制造系统》
EI
CSCD
北大核心
2015年第6期1476-1485,共10页
Computer Integrated Manufacturing Systems
基金
国家自然科学基金资助项目(71401019)
重庆市教委人文社会科学研究资助项目(14SKG05)
重庆市教委科学技术研究资助项目(KJ100413)~~
关键词
混流装配线
多目标优化
遗传算法
mixed-model assembly line
multi-objective optimization
genetic algorithms
作者简介
韩煜东（1975-），男，甘肃兰州人，重庆交通大学副教授，研究方向：工业工程与管理，E-mail：hanyudong@gmail．com
董双飞（1989-），男，重庆梁平人，重庆交通大学研究生，研究方向：企业运作管理与流程再造；
谭柏川（1986-），男，四川平昌人，重庆交通大学研究生，研究方向：物流配送、智能算法。
