A genetic algorithm for machine scheduling problem under shared resource constraints

  • Authors:
  • Yanzhi Li;Fan Wang;Andrew Lim

  • Affiliations:
  • Department of Industrial Engineering and Engineering Management, Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong.;Department of Industrial Engineering and Engineering Management, Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong.;Department of Industrial Engineering and Engineering Management, Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong

  • Venue:
  • International Journal of Computer Applications in Technology
  • Year:
  • 2004

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Abstract

In this paper, we present a popular machine scheduling problem with resource constraints in manufacturing engineering. A genetic algorithm based approach is put forward and illustrated, including a specialised encoding and two kinds of decoding greedy schemes. Compared with both several kinds of lower bounds we present in this paper and the results from ILOG OPL software package, it is shown that our rapid genetic algorithm achieved significant results with stable and near-optimal performance.