作业时间依赖顺序的拆卸线平衡多目标优化

在废旧产品拆卸时无先后关系约束的任务之间可能存在拆卸干扰，使任务作业时间依赖于拆卸顺序，导致产品总作业时间不确定，从而影响拆卸线的平衡。为此，考虑拆卸过程中任务间的相互干扰，以最小化拆卸成本和环境危害为目标，构建作业时间依赖顺序的拆卸线平衡多目标优化模型，并提出一种Pareto人工蜂群算法进行求解，采用混合生成法保证种群质量与多样性，设计变邻域深度搜索策略以提高雇佣蜂局部开采效率，为降低侦察蜂探测的盲目性采用基于外部存档的单点变异算子进行搜索。最后通过算例与实例验证算法的有效性以及平衡任务在拆卸线上分配的重要性。

Multi-objective Optimization for Disassembly Line Balancing Problem with Sequence-dependent Part Removal Times

Remanufacturing is an effective way to realize the reutilization of resources. Disassembly plays a key role in remanufacturing since it allows for the selective separation of desired parts from the end-of-life (EOL) products. Disassembly line is the best choiceto deal with EOL products on a large scale, so it is essential that it be designed and balanced to work efficiently. However, in the disassembly process, some parts may interact with each other and their disassembly times will be incremented by additional operations, and this affects the balance of disassembly line. In order to solve the disassembly interference among parts, in this research a sequence-dependent disassembly line balancing problem is presented with two objectives including minimization of the disassembly cost and environmental hazards. Then, a Pareto artificial bee colony algorithm is proposed for addressing this multi-objective optimization problem. A mixed strategy is designed to build an initial population with high quality and diversity, and some improvements are made in local exploitation and global exploration to accelerate the search speed. Finally, aset of benchmark instances is used to test the performance of the proposed algorithm. Computational results evidently indicate the superior efficiency of the proposed algorithm.In addition, a case study is presented to illustrate that balancing the tasks among workstations can effectively avoid the tasks with more time increments being disassembled on priority.