A competent memetic algorithm for complex scheduling

Authors:
Miguel A. González;Camino R. Vela;Ramiro Varela
Affiliations:
A.I. Centre and Department of Computer Science, University of Oviedo, Oviedo, Spain;A.I. Centre and Department of Computer Science, University of Oviedo, Oviedo, Spain;A.I. Centre and Department of Computer Science, University of Oviedo, Oviedo, Spain
Venue:
Natural Computing: an international journal
Year:
2012

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Abstract

We face the job shop scheduling problem with sequence dependent setup times and makespan minimization by memetic algorithm. This algorithm combines a classic genetic algorithm with a local searcher. The performance of the local searcher relies on the combination of a tabu search algorithm with a neighborhood structure termed N S that are thoroughly described and analyzed. Also, two evolution models are considered: Lamarckian and Baldwinian evolution. We report results from an experimental study across conventional benchmark instances showing that the proposed algorithm outperforms the current state-of-the-art methods and that Lamarckian evolution is better than Baldwinian evolution.