A Grey Wolf Optimization Algorithm for Stochastic Multi-Objective Disassembly Line Balancing Problem

EasyChair Preprint 6809

Abstract

Outdated waste products need to obtain high profits in a short period of time in the process of recycling and disassembly. Uncertainty factor of product wear aging and disassembly sequence increase the risk of demolition failure, that involves the disassembly line balance problem(DLBP). This paper set up a model for maximizing disassembly profit and minimizing failure based on the AND/OR graph. For this purpose, we present a random multi-objective discrete Grey Wolf optimization algorithm. By radio example experiments, we found that the algorithm was superior to NSGA-II and MOEA/D, which proved the effectiveness and feasibility of the method.

Keyphrases: Disassembly time, disassembly failure cost, disassembly line balancing problem, disassembly profit, multi-objective optimization

@booklet{EasyChair:6809,
  author    = {Hanshuo Hui and Fuwei Wang and Weimin Wang and Ze Zhang and Meiqin Zuo and Fengting Li},
  title     = {A Grey Wolf Optimization Algorithm for Stochastic Multi-Objective Disassembly Line Balancing Problem},
  howpublished = {EasyChair Preprint 6809},
  year      = {EasyChair, 2021}}