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Hybrid Flowshop with Unrelated Machines, Sequence Dependent Setup Time and Availability Constraints: An Enhanced Crossover Operator for a Genetic Algorithm

  • Victor Yaurima
  • Larisa Burtseva
  • Andrei Tchernykh
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4967)

Abstract

This paper presents a genetic algorithm for a scheduling problem frequent in printed circuit board manufacturing: a hybrid flowshop with unrelated machines, sequence dependent setup time and machine availability constraints. The proposed genetic algorithm is a modified version of previously proposed genetic algorithms for the same problem. Experimental results show the advantages of using new crossover operator. Furthermore, statistical tests confirm the superiority of the proposed variant over the state-of-the-art heuristics.

Keywords

Genetic Algorithm Schedule Problem Setup Time Flow Shop Immune Algorithm 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  • Victor Yaurima
    • 1
  • Larisa Burtseva
    • 2
  • Andrei Tchernykh
    • 3
  1. 1.CESUES Superior Studies CenterSan Luis R.C.Mexico
  2. 2.Autonomous University of Baja CaliforniaMexicaliMexico
  3. 3.CICESE Research CenterEnsenadaMexico

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