为了实现以完工时间最短为目标的工艺规划与车间调度集成优化，提出了基于新编码遗传算法(Genetic Algorithm，GA)的集成优化方法。对工艺规划与车间调度集成优化(Integrated Process Planning and Scheduling optimization，IPPS)问题进行了描述，并建立了完工时间最短的集成优化模型;设计一种具有最大柔性空间的染色体编码方法，从编码角度保证了集成优化问题的最大柔性度;根据IPPS问题特定约束改进了交叉变异方法，保证遗传操作前后均为可行解，使算法迭代均为有效迭代;进而制定了基于新编码遗传算法的IPPS问题求解流程。经Kim算例验证可知，与现有先进算法两阶段混合算法(Two-stage Hybrid Algorithm，THA)、改进蚁群算法(Enhanced Ant Colony Algorithm，EACA)和混合遗传算法(Hybrid Genetic Algorithm，HGA)相比，新编码GA在小规模、大规模生产情况下集成优化方案的完工时间均最小(分别为343、344、372、320、427及432 min)，实验结果验证了新编码GA在IPPS问题求解中的可行性和先进性。
Process planning and workshop scheduling integrated optimization adopting new coding mode genetic algorithm
In order to achieve integrated optimization of process planning and workshop scheduling with the goal of minimizing completion time,a novel coding Genetic Algorithm(GA)based integrated optimization method was proposed.The Integrated Process Planning and Scheduling optimization(IPPS)problem was described and an integrated optimization model with minimi-zing completion time was established;a chromosome encoding method with maximum flexibility space was designed to ensure the maximum flexibility of integrated optimization problems from an encoding perspective;crossover and mutation method based on specific constraints of IPPS problem was improved,ensuring feasible solutions before and after genetic operation and making al-gorithm iterations effective;furthermore,a novel encoding genetic algorithm based IPPS problem solving process was developed.According to the verification of Kim example,compared with the existing advanced algorithms such as Two-stage Hy-brid Algorithm(THA),Enhanced Ant Colony Algorithm(EACA),Hybrid Genetic Algorithm(HGA),completion time opti-mized by the novel coding GA algorithm is the smallest(i.e.343,344,372,320,427,432 min respectively)in the case of small-scale and large-scale production.The experimental results verify that the novel coding GA algorithm in solving IPPS prob-lems is feasibility and progressiveness.
万方数据
维普
