Scheduling with Memetic Algorithms over the Spaces of Semi-active and Active Schedules

  • Miguel A. González
  • Camino R. Vela
  • Ramiro Varela
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4029)


The Job Shop Scheduling Problem is a paradigm of Constraint Satisfaction Problems that has interested to researchers over the last decades. In this paper we confront this problem by means of a Genetic Algorithm that is hybridized with a local search method. The Genetic Algorithm searches over the space of active schedules, whereas the local search does it over the space of semi-active ones. We report results from an experimental study over a set of selected problem instances showing that this combination of search spaces is better than restricting both algorithms to search over the same space. Furthermore we compare with the well-known Genetic Algorithms proposed by D. Mattfeld and the Branch and Bound procedure proposed by P. Brucker and obtain competitive results.


Genetic Algorithm Local Search Critical Path Constraint Satisfaction Problem Memetic 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 2006

Authors and Affiliations

  • Miguel A. González
    • 1
  • Camino R. Vela
    • 1
  • Ramiro Varela
    • 1
  1. 1.Artificial Intelligence CenterUniversity of OviedoSpain

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