Multi-objective line balancing problems and solution approaches: Considering multi-manned stations with heterogenous workers

Recycling plays a critical role in environmental sustainability and provides economic benefits. Disassembly, which is one of the recycling methods, can be defined as a systematic method to separate a product into its constituent parts, subgroups, or desired parts. In this study, the multi-objective disassembly line balancing problems are addressed by considering the workers' heterogeneity and group-based worker assignment strategy, which is an effective method in using time and resources. A novel optimization model is proposed to formulate the problems with the overall cost, cycle time, and workload imbalance objectives. In this context, while the improved version of the augmented ϵ-constrained (AUGMECON2) method is employed to solve small-sized problems, the non-dominated sorting genetic algorithm-II (NSGA-II) is adapted for large-sized problems. According to the computational results, high-quality solutions are achieved when the group-based assignment strategy is realized. From the results, it is observed that the skill levels of the workers do not cause any difference in the solutions. Besides, although it is not found as the statistically significant, the heterogeneous workers provide slightly better solutions compared to homogeneous workers.