Abstract:

Combining the characteristics of disassembly line, a mathematical model was established for multi-objective DLBP where several optimization objectives were considered, such as minimizing the number of workstations, balancing idle time at each workstation, removing hazardous, high demand components as early as possible and minimizing the disassembly direction changes,then, an improved ant colony optimization algorithm was developed. In this algorithm, a hybrid search mechanism by comprehensively considering utilization, exploration and random search was constructed. The remove time, the harm and the demand of parts of DLBP were collaboratively considered and used for the heuristic information of the proposed algorithm. Finally, the computer experiments on different scale test instances were performed and the results indicate the feasibility and validity of the proposed algorithm.

Key words: disassembly line balancing problem(DLBP), particle swarm algorithm, heuristic information;multi-objective optimization

摘要：

结合拆卸线平衡问题的特性,建立了相应的数学模型。该模型在以最小化工作站数、均衡各工作站空闲时间为目标函数的基础上,考虑了尽可能早地拆卸有危害、高需求的零件以及最小化拆卸方向的改变,提出了一种改进的蚁群算法。该算法采用了利用先验知识、探索新路径、随机选择三种方式的混合搜索机制,将综合考虑零件拆卸时间、危害和需求作为算法的启发式信息来提高搜索的效率。应用实例的计算分析表明该提算法具有可行性及有效性。

关键词: 拆卸线平衡, 蚁群算法, 启发式信息;多目标优化