多品种分批量冲压车间的耦合选择NSGA-Ⅱ调度优化

Multiple Varieties and Batches Stamping Workshop Scheduling Optimization Based on Coupling Selection NSGA-Ⅱ Algorithm

为了对多品种分批量生产的冲压车间调度方案进行优化,减少冲压车间的完工时间、加工成本和换模次数,提出了基于耦合选择NSGA-Ⅱ算法的冲压车间调度优化方法。对冲压车间的调度优化问题进行了数学描述,建立了多目标、多限制条件的优化模型。通过构造4基因链缠绕的染色体,将冲压车间调度优化问题转化为遗传算法的多目标搜索问题。在传统NSGA-Ⅱ算法基础上,将耦合选择策略引入到算法中,兼顾了染色体的优越性和多样性,从而提出了基于耦合选择NSGA-Ⅱ算法的调度优化方法。经验证,耦合选择NSGA-Ⅱ算法所得Pareto前沿解质量高于传统NSGA-Ⅱ算法所得Pareto前沿解质量。使用等权重系数法从Pareto解集中确定了最优解,与优化前相比,换模次数减少了52.2%,加工成本减少了18.4%,最大完工时间减少了40.0%,以上数据验证了耦合选择NSGA-Ⅱ算法在冲压车间调度优化中的可行性。

In order to optimize the scheduling scheme of stamping shop for multi variety and batch production,reduce the completion time,processing cost and die changing times of stamping workshop,a stamping workshop scheduling optimization method based on coupling selection NSGA-Ⅱ algorithm was proposed.In this paper,the mathematical description of the scheduling optimization problem of stamping shop is given,and a multi-objective and multi constraint optimization model is established.By constructing a chromosome with four gene chains,the optimization problem of stamping shop scheduling is transformed into a multiobjective search problem of genetic algorithm.Based on the traditional NSGA-Ⅱ algorithm,the coupling selection strategy is introduced into the algorithm,taking into account the superiority and diversity of chromosomes,thus a scheduling optimization method based on the coupling selection NSGA-Ⅱ algorithm is proposed.The results show that the quality of Pareto frontier solution of coupling selection NSGA-Ⅱ algorithm is higher than that of traditional NSGA-Ⅱ algorithm.The optimal solution is determined from Pareto solution set by equal weight coefficient method.Compared with before optimization,the number of die changing is reduced by 52.2%,the processing cost is reduced by 18.4%,and the maximum completion time is reduced by 40.0%.The above data verify the feasibility of coupling selection NSGA-Ⅱ algorithm in stamping shop scheduling optimization.