【摘要】 拆卸是废旧产品回收利用的重要途径，根据产品拆卸线的特点，构建拆卸线平衡问题的多目标关系。针对求解拆卸线平衡问题所遇到的求解结果单一、无法满足平衡诸多目标等问题，以均衡工作站负载且引入操作安全性、任务拆卸方向和任务需求为优化目标建立数学模型，在此基础上，提出一种基于遗传改进的多目标灰狼算法进行求解计算。基于废旧电冰箱拆卸案例对比验证算法的效果与性能，并将其应用于再制造企业某废旧电视机拆卸实例中。以Plant Simulation 15.0仿真软件为平台，运用仿真技术对所得理论方案分析与优化，通过在重要工位上建立缓冲区来解决实际拆卸过程中所存在的工位堵塞问题。结果表明该算法的收敛性较好，所获得非支配解集更逼近Pareto最优前沿，得出多个合理拆卸方案，为决策者选择拆卸方案提供了依据，且改善后的工位产能也提升了3.23%。更多还原

【Abstract】 Disassembly is an important way to recycle waste products. According to the characteristics of disassembly line, the multi-objective relationship of disassembly line balance problem is constructed. In order to solve the disassembly line balance problem, the solution result is single and can not meet the balance of many objectives, and so on, a mathematical model was established to balance the workstation load,introduced the operation safety, task disassembly direction and task requirements as the optimization objectives. On this basis, a genetically improved multi-objective gray wolf algorithm was proposed to solve the calculation. The effect and performance of the algorithm were verified by a disassembly case of an old refrigerator, and it was applied to a disassembly case of an old TV set in a remanufacturing enterprise. Using Plant Simulation 15.0 simulation software as a platform, the simulation technology was used to analyze and optimize the theoretical scheme obtained. By establishing buffer on the important stations, the station blockage problem existed in the actual disassembly process was solved.The results show that the convergence of the algorithm is good, the non-dominated solution set is closer to the Pareto optimal frontier, and multiple reasonable disassembly schemes are obtained, which provides a basis for decision makers to choose disassembly schemes. Moreover,the improved station productivity is also increased by 3.23%.更多还原