Multi-objective shuffled frog leading algorithm for human-robot collaborative disassembly line balancing problems

Disassembly line plays a crucial role in the recycling of end-of-life products, which can effectively reduce the pressure of resource shortage. Considering the development of intelligent plant, this paper studies the human-robot collaborative disassembly line balancing problem with the optimization objectives of maximizing total profit and minimizing energy consumption. The disassembly process is specified with the AND/OR graph model. In addition, a Pareto improved multiobjective shuffled frog leading algorithm is proposed, which introduces an elitist strategy to improve the searching ability. Finally, the proposed model and algorithm are applied to instances of human-robot collaborative disassembly lines. Through different comparison experiments with the nondominated sorting genetic algorithm II and harmony search, the superiority of the proposed algorithm in performance and quality is verified.