摘要
产品拆卸过程中零部件之间会相互干扰影响任务作业时间,基于该情形构建了多目标U型SDDLBP优化模型,并提出一种自适应ABC算法。所提算法设计了自适应动态邻域搜索方法,以提高局部开发能力;采用了轮盘赌与锦标赛法结合的分段选择法,以有效评价并选择蜜源进行深度开发;建立了基于当前最优解的变异操作,以提高全局探索能力快速跳出局部最优。最后,通过算例测试和实例分析验证算法的高效性。
Considering interactions among precedence-free tasks in the disassembly process,a multi-objective U-shaped SDDLBP is presented,and a self-adaptive ABC algorithm is developed to solve it.In order to enhance the capability of local exploration,a dynamic neighborhood search method is proposed.A multi-stage evaluation method of roulette wheel selection and tournament selection is used to effectively choose food sources for further exploration.The mutation operator based on the current best solution is designed to improve the global exploitation and jump out of the local optimum rapidly.Finally,the performance of the proposed algorithm is tested by a set of benchmark instances and two case scenarios.Computational results indicate that the proposed algorithm has superior performance.
作者
王书伟
郭秀萍
刘佳
WANG Shu-wei;GUO Xiu-ping;LIU Jia(School of Economics & Management,Southwest Jiaotong University,Chengdu 610031 China;BusinessSchool,Qingdao University of Technology,Qingdao 266520 China)
出处
《运筹与管理》
CSSCI
CSCD
北大核心
2019年第3期104-110,共7页
Operations Research and Management Science
基金
国家自然科学基金资助项目(71471151)
中央高校基本科研业务费专项资金(26816WCX04)
关键词
U型拆卸线
顺序相依
ABC算法
动态邻域搜索
U-shaped disassembly line
sequence-dependent
artificial bee colony algorithm
dynamic neighborhood search
