基于改进NSGA-Ⅱ算法求解混流装配线平衡问题
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摘要
针对混流制造系统装配线平衡和物料配送车辆路径优化问题,从优化目标、影响因素和约束条件等方面,建立了以装配线平衡最小均衡系统、物料小车最短行驶距离和最小车辆利用率最大为优化目标的多目标混流装配线模型。根据问题的具体情况,设计了一种基于生态进化策略的NSGA-Ⅱ算法,该算法定义了一种环境自检算子用于检测环境是否变化,主体种群与选择后经过交叉、变异后面对环境变化的种群进行竞争,迭代过程中种群内捕食与被捕食的竞争以促进种群多样性及不断提高生存力,算法采用0~1编码,通过具体混流装配系统中实例验证了所建模型和算法的有效性。
To sovle the problem of mixed-model assembly line balancing and material distribution not matching,analyzed the optimization of the goal,influence factors and the constraint condition,set up the model of assembly line balancing minimum equilibrium coefficient,the shortest distance of material car,the maximum and minimum vehicle utilization of multi-objective mixed flowassembly line. According to the actual circumstances of the problem,designed an improved NSGA-Ⅱ algorithm based on ecological strategy,the algorithm defines an environment self-checking operator which used to test environment changed or not,subject populations and after crossover and mutation populations competed in the face of environmental changed to promote the population diversity and improve survivability,put forward the coding of 0 ~ 1,fanally,through an example verify the effectiveness of the model and algorithm.
To sovle the problem of mixed-model assembly line balancing and material distribution not matching,analyzed the optimization of the goal,influence factors and the constraint condition,set up the model of assembly line balancing minimum equilibrium coefficient,the shortest distance of material car,the maximum and minimum vehicle utilization of multi-objective mixed flowassembly line. According to the actual circumstances of the problem,designed an improved NSGA-Ⅱ algorithm based on ecological strategy,the algorithm defines an environment self-checking operator which used to test environment changed or not,subject populations and after crossover and mutation populations competed in the face of environmental changed to promote the population diversity and improve survivability,put forward the coding of 0 ~ 1,fanally,through an example verify the effectiveness of the model and algorithm.
引文
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[3]龚轲,丁武学,王栓虎.有兼容作业元素的混流装配线平衡问题研究[J].组合机床与自动化加工技术,2015(6):134-136.
[4]吴永明,戴隆州,李少波,等.基于改进粒子群优化算法的混流装配线演进平衡[J].计算机集成制造系统,2017,23(4):781-790.
[5]蒋南云,葛红玉,方叶祥,等.基于Flexsim的随机混流装配线平衡设计与仿真[J].组合机床与自动化加工技术,2014(12):128-130.
[6]韩煜东,董双飞,谭柏川.基于改进遗传算法的混装线多目标优化[J].计算机集成制造系统,2015,21(6):1476-1485.
[7]张则强,余庆良,胡俊逸,等.随机混流装配线平衡问题的一种混合粒子群算法[J].机械设计与研究,2013,29(2):60-63.
[8]Deb K,Pratap A,Agarwal S,et al.A Fast and Elitist Multiobjective Gentic Algorithm:NSGA-II[J].IEEE Trans.on Evolutionary Computation,2002,6(2):182-197.
[9]吴永明,戴隆州,罗利飞,等.求解第Ⅱ类装配线平衡的改进粒子群算法[J].机械设计与制造,2017(2):124-127.
[10]夏季,华志刚,彭鹏,等.基于非支配排序遗传算法的无约束多目标优化配煤模型[J].中国电机工程学报,2011,31(2):85-90.
[2]李金霖,高杰,孙林岩.考虑需求波动和产能调整成本的混流装配线平衡问题[J].系统工程理论与实践,2014,34(1):70-76.
[3]龚轲,丁武学,王栓虎.有兼容作业元素的混流装配线平衡问题研究[J].组合机床与自动化加工技术,2015(6):134-136.
[4]吴永明,戴隆州,李少波,等.基于改进粒子群优化算法的混流装配线演进平衡[J].计算机集成制造系统,2017,23(4):781-790.
[5]蒋南云,葛红玉,方叶祥,等.基于Flexsim的随机混流装配线平衡设计与仿真[J].组合机床与自动化加工技术,2014(12):128-130.
[6]韩煜东,董双飞,谭柏川.基于改进遗传算法的混装线多目标优化[J].计算机集成制造系统,2015,21(6):1476-1485.
[7]张则强,余庆良,胡俊逸,等.随机混流装配线平衡问题的一种混合粒子群算法[J].机械设计与研究,2013,29(2):60-63.
[8]Deb K,Pratap A,Agarwal S,et al.A Fast and Elitist Multiobjective Gentic Algorithm:NSGA-II[J].IEEE Trans.on Evolutionary Computation,2002,6(2):182-197.
[9]吴永明,戴隆州,罗利飞,等.求解第Ⅱ类装配线平衡的改进粒子群算法[J].机械设计与制造,2017(2):124-127.
[10]夏季,华志刚,彭鹏,等.基于非支配排序遗传算法的无约束多目标优化配煤模型[J].中国电机工程学报,2011,31(2):85-90.