A Discrete Artificial Bee Colony Algorithm for Multiobjective Disassembly Line Balancing of End-of-Life Products

Disassembly lines are the most effective way to address large-scale value recovery from end-of-life (EOL) products. Disassembly line balancing (DLB) greatly affects the economics and throughput of EOL product processing. Complete disassembly is generally not suitable for disassembly enterprises; most often, the maximum profit is realized through partial disassembly. Thus, this article proposes a partial disassembly method and establishes a new DLB model that addresses both economic benefits and environmental impacts. The objective of the model is to maximize the effectiveness of workers, increase profit, reduce energy consumption, and balance the loads of workers. Moreover, the model considers the impact of disassembly face and tool changes on the disassembly process. A discrete multiobjective artificial bee colony (MOABC) algorithm is developed, and it takes the precedence constraints into account to obtain the Pareto solutions. The MOABC algorithm is applied to the disassembly lines of two real-world EOL products, including those of an LCD TV and a refrigerator. Experiments show that the performance of the MOABC algorithm is better than those of five well-known multiobjective algorithms. The proposed model and method can provide multiple disassembly schemes for decision makers of disassembly enterprises based on their preferences.