Multi-objective Disassembly Line Balancing Problem Based on Pareto Improved Cat Swarm Optimization Algorithm

We propose an improved cat swarm optimization algorithm to solve the multi-objective disassembly line balancing problem. The disassembly line balancing problem takes disassembly sequence as code. In accordance with this characteristic, we propose a searching model based on a random number and fixed perturbation to ensure that the cat performs the random search near the current position. The cross operation and the mutation operation of the genetic algorithm are introduced in the tracking model of the cat swarm optimization algorithm to guide the proposed algorithm to approach the global optimum and to avoid the prematurity of the traditional cat swarm optimization algorithm. The establishment of an external file and the adoption of the elitism strategy speed up the convergence rate of the algorithm. We apply the proposed algorithm to solve the class multi-objective disassembly line balancing problem and compare it with other algorithms. Our findings verify the effectiveness of the proposed algorithm.