求解第Ⅱ类装配线平衡问题的混合遗传算法  

Hybrid genetic algorithm for assembly line balancing-Ⅱproblem

作　　者：麻娟 刘俨后 楚满福 高军[1] MA Juan;LIU Yanhou;CHU Manfu;GAO Jun(School of Mechanical Engineering, Shandong University of Technology, Zibo 255049, China)

机构地区：[1]山东理工大学机械工程学院,山东淄博255049

出　　处：《山东理工大学学报（自然科学版）》2019年第3期55-59,共5页Journal of Shandong University of Technology:Natural Science Edition

基　　金：山东省自然科学基金项目(ZR2017BEE048)

摘　　要：针对第Ⅱ类装配线平衡问题,提出一种混合遗传算法,以解决典型遗传算法易陷入局部最优解的问题。在混合遗传算法中,引入烟花算法爆炸算子中基于免疫浓度思想,并与典型遗传算法的精英保留策略相结合,以保持进化过程中种群多样性,避免算法陷入局部最优,提高了全局寻优的能力;同时将邻域搜索策略引入变异算子,以改进算法的局部搜索性能。通过算例验证了本文算法的有效性,与典型遗传算法相比,该算法寻优率提高了1.4倍,求解时间减少了25.8%,为装配线平衡问题的解决提供了一种新方法。Aiming at assembly balancing-Ⅱ problem, a hybrid genetic algorithm is proposed to avoid trapping in local optimum which is a disadvantage of standard genetic algorithm. The immune concentration of fireworks algorithm is combined with the elitist strategy into hybrid genetic algorithm,in order to maintain population diversity, and to get better global search ability to avoid the local optimal solution. Furthermore, variable neighborhood search is also added in this algorithm, which can get better local search ability. Experiment is carried out, and the result verifies the effectiveness of hybrid genetic algorithm. The success rate is as 2.4 times high as typical genetic algorithm, and the computation time is reduced by 25.8%. This algorithm provides a new way to solve assembly balancing problem.

关 键 词：装配线平衡 遗传算法 免疫浓度 邻域搜索 

分 类 号：TH166[机械工程—机械制造及自动化] F406[经济管理—产业经济]