A discrete differential evolution algorithm for the permutation flowshop scheduling problem

  • Authors:

  • Quan-Qe Pan;Mehmet Fatih Tasgetiren;Yun-Chia Liang

  • Affiliations:

  • Liaocheng University;Sultan Qaboos University;Yuan Ze University

  • Venue:
  • Proceedings of the 9th annual conference on Genetic and evolutionary computation
  • Year:
  • 2007

Quantified Score

Hi-index 0.00

Visualization

Abstract

In this paper, a novel discrete differential evolution (DDE) algorithm is presented to solve the permutation flowhop scheduling problem with the makespan criterion. The DDE algorithm is simple in nature such that it first mutates a target population to produce the mutant population. Then the target population is recombined with the mutant population in order to generate a trial population. Finally, a selection operator is applied to both target and trial populations to determine who will survive for the next generation based on fitness evaluations. As a mutation operator in the discrete differential evolution algorithm, a destruction and construction procedure is employed to generate the mutant population. We propose a referenced local search, which is embedded in the discrete differential evolution algorithm to further improve the solution quality. Computational results show that the proposed DDE algorithm with the referenced local search is very competitive to the iterated greedy algorithm which is one of the best performing algorithms for the permutation flowshop scheduling problem in the literature.