Multi-objective optimisation of stochastic hybrid production line balancing including assembly and disassembly tasks
研究了同时包含装配和拆卸任务的混合生产线平衡问题，考虑任务时间的不确定性，提出一种结合变邻域搜索和非支配排序遗传算法的混合算法，并通过案例验证了混合生产线的优势。
Assembly and disassembly are important activities in the manufacturing/remanufacturing process. Although the line balancing problems of them have been extensively discussed in the existing literature, they are rarely integrated into one system. In this paper, a hybrid production line balancing problem is adopted while considering the similarity between the assembly and disassembly tasks. First, to better reflect the uncertainty existing in the actual production environment, a mathematical model of the multi-objective stochastic hybrid production line balancing problem is presented, in which task disassembly times are assumed to be random variables with known normal probability distributions. Then, a hybrid VNS-NSGA II algorithm combining variable neighbourhood search (VNS) and non-dominated sorting genetic algorithm II (NSGA II) is proposed to solve the problem. VNS is embedded into NSGA II as a local search to improve the quality of the solutions found by the NSGA II at each generation. Finally, the effectiveness of the proposed method is verified by a case study, and the superiority of hybrid production line is reflected by comparing the solutions of the independent production line with the hybrid production line. Computational comparisons demonstrate the potential benefits of the hybrid production line and the proposed method.