Soft Computing

, Volume 16, Issue 12, pp 2097–2113 | Cite as

An efficient hybrid evolutionary algorithm for scheduling with setup times and weighted tardiness minimization

  • Miguel Ángel González
  • Inés González-Rodríguez
  • Camino R. Vela
  • Ramiro Varela
Original Paper

Abstract

We confront the job shop scheduling problem with sequence-dependent setup times and weighted tardiness minimization. To solve this problem, we propose a hybrid metaheuristic that combines the intensification capability of tabu search with the diversification capability of a genetic algorithm which plays the role of long term memory for tabu search in the combined approach. We define and analyze a new neighborhood structure for this problem which is embedded in the tabu search algorithm. The efficiency of the proposed algorithm relies on some elements such as neighbors filtering and a proper balance between intensification and diversification of the search. We report results from an experimental study across conventional benchmarks, where we analyze our approach and demonstrate that it compares favorably to the state-of-the-art methods.

Notes

Acknowledgments

This research has been supported by the Spanish Government under research grants FEDER TIN2010-20976-C02-02 and MTM2010-16051.

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Copyright information

© Springer-Verlag 2012

Authors and Affiliations

  • Miguel Ángel González
    • 1
  • Inés González-Rodríguez
    • 2
  • Camino R. Vela
    • 1
  • Ramiro Varela
    • 1
  1. 1.Department of Computing, Artificial Intelligence Center, Computing Technologies GroupUniversity of OviedoGijónSpain
  2. 2.Department of Mathematics, Statistics and ComputingUniversity of CantabriaCantabriaSpain

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