GA/TS: A hybrid approach for job shop scheduling in a production system

  • José Ramón Zubizarreta Aizpuru
  • Javier Arrieta Usunáriz
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 990)


This paper outlines a new efficient approach to solve combinatorial optimization problems making use of a hybrid search method. The approach integrates genetic algorithms (GA) and tabu search (TS) techniques to be incorporated into a generic architecture for a knowledge-based manufacturing system.

In this paper, a new method, called GA/TS, has been developed. The proposed method pursues a hybrid schedule generation strategy wherein it effectively combines knowledge acquired via genetics-based induction with tabu search methodology. We have used this hybrid approach to explore new strategies that may result in more powerful solution methods. Experiments on randomly generated problems of practical complexity, the notorious 10×10 instance of Muth&Thompson's benchmark and several instances of Lawrence [22] show that the hybrid scheduler strategy produces good results, better than previous efforts using genetics algorithms, and comparable to existing search-based methods [2, 4, 21].


Genetic algorithms production scheduling tabu search 


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Copyright information

© Springer-Verlag Berlin Heidelberg 1995

Authors and Affiliations

  • José Ramón Zubizarreta Aizpuru
    • 1
  • Javier Arrieta Usunáriz
    • 1
  1. 1.Facultad de InformáticaUniversidad del País VascoSan SebastiánSpain

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