基于SEGA算法的区段式车间系统协同布局优化

A Collaborative Optimization Method for Segmented Workshop System Based on Strengthen Elitist Genetic Algorithm

针对区段式车间设备布局与搬运路径协同优化建模涉及的参数变量复杂、约束多等问题,研究车间系统协同优化建模与求解方法。分析区段式车间系统特征和工艺流程,提出考虑装卸点位置的重载和空载搬运距离计算方法;采用多点离散分布描述产品需求的不确定性,以AGV重载和空载运行总成本最小为目标,建立设备布局与AGV路径规划协同优化模型;结合适应度函数线性尺度变换、精英锦标赛选择等策略,设计基于双链染色体编码的增强精英保留遗传算法。实例研究表明,提出的协同优化模型和求解算法能有效解决区段式车间系统布局规划问题。

In order to solve the problems of complex parameter variables and constraints involved in the collaborative optimization modeling of equipment layout and handling path planning in segmented flow topology(SFT)workshop system,the modeling and solving method of workshop system collaborative optimization was studied.Analyzing the system characteristics and process flow of SFT workshop system,and the calculation method of heavy load and no-load handling distance considering the position of loading and unloading points was proposed.The multi-point discrete distribution was adopted to describe the uncertainty of product demand in the dynamic environment.A collaborative optimization model of workshop equipment layout and AGVs path planning under uncertain requirements was established,with the objective of minimizing the total cost of heavy-load and no-load trip cost of AGVs.Combining the strategies of linear scaling of fitness function and selection of elite tournaments,a strengthen elitist genetic algorithm(SEGA)based on double stranded chromosome coding was designed.Case study shows that the proposed collaborative optimization model and algorithm can solve the workshop layout planning problem effectively.