Genetic Bat Algorithm-Based Multi-Objective Selective Disassembly Sequence Planning

Abstract

The genetic bat algorithm is being actively investigated for its application in the complex multi-objective product selective disassembly sequence planning problem. To broaden the scope of the search space and enhance the overall search efficiency, the traditional bat algorithm has undergone discretization, incorporating a cross-mutation mechanism into the construction of the fitness function model. To assess the efficacy of this novel approach, an industrial mechanical arm is utilized as a representative case study. Upon comparison with the traditional bat algorithm, the proposed method exhibits shorter convergence times across a range of population sizes, thus validating its effectiveness.