Multi-Objective Multi-Verse Optimizer for Multi-Product Partial U-Shaped Disassembly Line Balancing Problem

The development of industry and technology promotes the acceleration of product replacement, and generate a large number of end-of-life products. Meanwhile, robots also play a significant role in disassembly. This paper proposes a scheme to solve a U-shaped disassembly line balancing problem with robots. A mathematical model for maximizing profits and minimizing carbon emissions is established. Then, the paper proposes an improved Multi-Objective Multi-Verse Optimizer (MOMVO) to solve the problem. Taking the disassembly of ballpoint pen and hammer drill as examples, our method is compared with Non-dominated Sorting Genetic Algorithm II (NSGA-II), Multi-Objective Evolutionary Algorithm based on Decomposition (MOEA/D), and Multi-Objective Cellular Genetic Algorithm (MOCGA). Comparison indexes include Inverted Generational Distance+ (IGD+) and hypervolume epsilon metric. The experimental results show that the MOMVO algorithm performs better than others on the U-shaped and robotic disassembly line.