Approach of Solving Dual Resource Constrained Multi-Objective Flexible Job Shop Scheduling Problem Based on MOEA/D

Abstract

With considering the scheduling objectives such as makespan, machine workload and product cost, a dual resource constrained flexible job shop scheduling problem is described. To solve this problem, a multi-objective evolutionary algorithm based on decomposition (MOEA/D) was proposed to simplify the solving process, and an improved differential evolution algorithm was introduced for evolving operation. A special encoding scheme was designed for the problem characteristics, the initial population was generated by the combination of random generation and strategy selection, and an improved crossover operator was applied to achieve differential evolution operations. At last, actual test instances of flexible job shop scheduling problem were tested to verify the efficiency of the proposed algorithm, and the results show that it is very effective.