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A competent memetic algorithm for complex scheduling

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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.

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Acknowledgments

This work has been supported by the Spanish Ministry of Science and Education under research project MEC-FEDER TIN2010-20976-C02-02 and by FICYT under grant BP07-109.

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Authors and Affiliations

  1. A.I. Centre and Department of Computer Science, University of Oviedo, Oviedo, Spain

    Miguel A. González, Camino R. Vela & Ramiro Varela

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  1. Miguel A. González
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  2. Camino R. Vela
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  3. Ramiro Varela
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Correspondence to Ramiro Varela.

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González, M.A., Vela, C.R. & Varela, R. A competent memetic algorithm for complex scheduling. Nat Comput 11, 151–160 (2012). https://doi.org/10.1007/s11047-011-9300-y

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