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MOEA/DEP: An Algebraic Decomposition-Based Evolutionary Algorithm for the Multiobjective Permutation Flowshop Scheduling Problem

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Evolutionary Computation in Combinatorial Optimization (EvoCOP 2018)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 10782))

Abstract

Algebraic evolutionary algorithms are an emerging class of meta-heuristics for combinatorial optimization based on strong mathematical foundations. In this paper we introduce a decomposition-based algebraic evolutionary algorithm, namely MOEA/DEP, in order to deal with multiobjective permutation-based optimization problems. As a case of study, MOEA/DEP has been experimentally validated on a multiobjective permutation flowshop scheduling problem (MoPFSP). In particular, the makespan and total flowtime objectives have been investigated. Experiments have been held on a widely used benchmark suite, and the obtained results have been compared with respect to the state-of-the-art Pareto fronts for MoPFSP. The experimental results have been analyzed by means of two commonly used performance metrics for multiobjective optimization. The analysis clearly shows that MOEA/DEP reaches new state-of-the-art results for the considered benchmark.

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Notes

  1. 1.

    In our previous paper [9] there was a typo. Actually, the time complexity of \( RandSS \) is \(\varTheta (n)\) and not \(\varTheta (n^2)\) as erroneously in [9]. A simple amortized analysis proves the claim.

  2. 2.

    https://github.com/murilozangari.

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Authors and Affiliations

  1. Department of Mathematics and Computer Science, University of Perugia, Perugia, Italy

    Marco Baioletti, Alfredo Milani & Valentino Santucci

  2. Department of Computer Science, Hong Kong Baptist University, Kowloon Tong, Hong Kong

    Alfredo Milani

Authors
  1. Marco Baioletti
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  2. Alfredo Milani
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  3. Valentino Santucci
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Correspondence to Valentino Santucci .

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Editors and Affiliations

  1. University of Lille, Lille, France

    Arnaud Liefooghe

  2. University of Manchester, Manchester, United Kingdom

    Manuel López-Ibáñez

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Baioletti, M., Milani, A., Santucci, V. (2018). MOEA/DEP: An Algebraic Decomposition-Based Evolutionary Algorithm for the Multiobjective Permutation Flowshop Scheduling Problem. In: Liefooghe, A., López-Ibáñez, M. (eds) Evolutionary Computation in Combinatorial Optimization. EvoCOP 2018. Lecture Notes in Computer Science(), vol 10782. Springer, Cham. https://doi.org/10.1007/978-3-319-77449-7_9

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  • DOI: https://doi.org/10.1007/978-3-319-77449-7_9

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