A genetic simulated annealing algorithm for parallel partial disassembly line balancing problem

The timely recovery and disassembly of waste electrical and electronic equipment (WEEE) can not only obtain a higher economic benefit but also can reduce the impact of hazardous substances on the environment. The parallel disassembly line can disassemble different kinds of WEEE synchronously and improve disassembly efficiency. Therefore, a parallel partial disassembly line balancing model with stochastic disassembly time is established in this paper. The evaluation indexes of the disassembly line include the number of workstations, workload smoothness, and disassembly profits. A new genetic simulated annealing algorithm is proposed to optimize the model. The encoding and decoding strategies are constructed according to the characteristics of partial disassembly and parallel layout. Two-point mapping crossover and single-point insertion mutation operations are designed to ensure that the disassembly sequence meets the precedence constraints and disassembly constraints. The simulated annealing operation is applied to the results of the genetic operation. The proposed algorithm obtains better solutions than the tabu search algorithm in stochastic parallel assembly line balancing problems, and the proposed algorithm has better performance than the CPLEX solver, genetic algorithm, and simulated annealing in parallel disassembly line balancing problems. Finally, a parallel partial disassembly line for waste televisions and refrigerators is constructed, and the performance of the proposed multi-objective algorithm is superior to those of five classical multi-objective algorithms. The results show that the proposed model has a better practical application ability and that the proposed algorithm can improve the performance of disassembly lines.