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Hybrid Tabu Search for Fuzzy Job Shop

  • Juan José Palacios
  • Jorge Puente
  • Inés González-Rodríguez
  • Camino R. Vela
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7930)

Abstract

We consider the fuzzy job shop scheduling problem, which is a variant of the well-known job shop problem, with uncertainty in task durations that we model using fuzzy numbers. We propose a tabu search algorithm for minimising the expected makespan based on reversing arcs within critical blocks. We test the algorithm and then combine it with a genetic algorithm from the literature so we can observe the synergy effect, obtaining better results with the hybrid algorithm than with its components by separate. Finally we compare our hybrid algorithm with a memetic algorithm from the literature and show that even in similar times, our method is better in terms of expected makespan.

Keywords

Local Search Fuzzy Number Tabu Search Memetic Algorithm Tabu List 
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 2013

Authors and Affiliations

  • Juan José Palacios
    • 1
  • Jorge Puente
    • 1
  • Inés González-Rodríguez
    • 2
  • Camino R. Vela
    • 1
  1. 1.A.I. Centre and Department of Computer ScienceUniversity of OviedoSpain
  2. 2.Department of Mathematics, Statistics and ComputingUniversity of CantabriaSpain

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