An Improved Genetic Algorithm for Job Shop Scheduling Problem

  • Authors:
  • Ren Qing-dao-er-ji;Yuping Wang;Xiaojing Si

  • Affiliations:
  • -;-;-

  • Venue:
  • CIS '10 Proceedings of the 2010 International Conference on Computational Intelligence and Security
  • Year:
  • 2010

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Abstract

Job shop scheduling problem is a typical NP-hard problem. In this paper, new designed crossover and mutation operators based on the characteristic of the job shop problem itself are specifically designed. Based on these, an improved genetic algorithm is proposed. The computer simulations are made on a set of benchmark problems and the results indicate the effectiveness of the proposed algorithm.