Minimizing energy consumption in multi-objective two-sided disassembly line balancing problem with complex execution constraints using dual-individual simulated annealing algorithm.

The increasing number of large-scale end-of-life products, such as vehicles and refrigerators have paid a negative impact on the ecological environment and led to the waste of non-renewable resources. The two-sided disassembly line is playing an important role in the recycling of end-of-life products with high efficiency. However, the complex execution constraints in the disassembly process have been ignored, and the additional energy consumption caused by hazardous tasks is not fully considered. Therefore, we introduce the two-sided disassembly line balancing problem with complex execution constraints and establish an improved mixed-integer programming model to optimize the weighted length, workload smoothness index, and total energy consumption simultaneously. A dual-individual simulated annealing algorithm with multi-objective is developed, in which two different neighbor structure strategies and a two-point mapping information exchange mechanism are designed to enrich the diversity of Pareto-optimal solutions. Six testing benchmark problems of different scales are designed, then the algorithm is evaluated with the single-objective and multi-objective simulated annealing and the famous NSGA-II. The results indicate that the proposed model and algorithm can satisfy the complex execution constraints for task assignment, effectively improve the smoothness index, and reduce the energy consumption in the disassembly system. [ABSTRACT FROM AUTHOR]