摘要
为提高车间的生产效率、降低成本,对设备布局进行优化是十分必要的。基于物流费用最小和面积利用率最大的原则,并增加辅助设施(上下料机器人)对布局的约束,建立了曲轴自动化生产车间设备布局的多目标优化模型;采用自适应遗传算法(adaptive genetic algorithm,AGA)求解该问题时,交叉、变异概率基于Logistic曲线自适应调整,有利于优胜劣汰和全局最优解的获得。与改造前的布局相比较,加入机器人后的优化布局使物流费用降低、占地面积减小,对企业降本增效具有一定现实意义。
It is necessary to optimize the facility layout,which can improve the production efficiency and reduce the cost. A multi-objective optimization model for the facility layout of crankshaft automation workshop was created： it was based on the principles of minimum material transport cost and maximum workshop area utilization,also added the constraint of auxiliary devices（ loading and unloading robots）. A kind of adaptive genetic algorithm（ AGA） was used to find the best solution of this model. The crossover and mutation probability based on the Logistic curve could adjust adaptively,which was advantageous to the evolution and the global optimal solution. Compared with the old layout,the optimized layout including the added robots makes the logistics cost less and the footprint decrease,which has certain significance for the enterprise to reduce the cost and improve the efficiency.
出处
《组合机床与自动化加工技术》
北大核心
2017年第12期151-155,共5页
Modular Machine Tool & Automatic Manufacturing Technique
基金
国家04科技重大专项(2015ZX04005006)
广东省科技重大专项(2014B090921004
2015B010918002)
中山市科技重大项目(2016F2FC0006)
关键词
设备布局
自适应遗传算法
多目标优化
facility layout
adaptive genetic algorithm
multi-objective optimization
