Multi-Man–Robot Disassembly Line Balancing Optimization by Mixed-Integer Programming and Problem-Oriented Group Evolutionary Algorithm

Abstract

Disassembly production lines that employ shared stations with multiple workers and robots are ideal for addressing obsolete products with complex structures and hazardous parts. In this study, a multiproduct multi-man–robot disassembly line balancing problem (MPMMR-DLBP) is developed and its mixed-integer programming model (MIPM) is established to minimize the number of stations, idle balancing index of operators (workers and robots), and the number of operators. In addition, a problem-oriented group evolutionary (POGE) algorithm is proposed to efficiently solve the MPMMR-DLBP. The proposed POGE develops a new “1+3” encoding mode and a heuristic decoding strategy based on the shortest time to complete tasks to construct a one-to-one correspondence between encoding sequences and disassembly schemes. Moreover, a reassociation evolution operation (REO) and a mapping crossover operation (MCO) are designed to generate new solutions and allow the population to evolve to the global optimum. Subsequently, the correctness of MIPM and the performance of POGE are verified using two small-scale cases. Finally, an actual MPMMR-DLBP for the mixed disassembly of refrigerators, microwave ovens, and dishwashers is optimized by POGE. A comparison of the optimized results with the other three common algorithms shows that the POGE is superior in the large-scale MPMMR-DLBP, and multiple optimized disassembly schemes are provided for decision makers.