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An Application of Generalized Strength Pareto Evolutionary Algorithm for Finding a Set of Non-Dominated Solutions with High-Spread and Well-Balanced Distribution in the Logistics Facility Location Problem

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Artificial Intelligence and Soft Computing (ICAISC 2017)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 10245))

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Abstract

The paper presents an application of generalized Strength Pareto Evolutionary Algorithm (SPEA) in the Logistic Facilities Location (LFL) problem. The task is to optimize a distribution network, i.e. the number of distribution centers and their locations as well as the number of clients served by the particular centers in terms of three following contrary/contradictory criteria: (a) the total maintenance cost of the network, (b) carbon emissions emitted by combustion engines of trucks into the atmosphere (subjects to minimization) and (c) the customer service reliability (subject to maximization). For this purpose, an original multi-objective optimization technique which allow to obtain a set of so-called non-dominated solutions of the considered problem, representing different levels of compromise between the above criteria, is applied. In order to provide a broad, flexible selection of the final solution from the obtained set, the proposed approach aims at finding the set of solutions with high spread and well-balanced distribution in the objective (criteria) space. The functionality of our technique is demonstrated using numerical experiments. Its distinct advantages over alternative approaches are presented in the frame of comparative analysis as well.

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Authors and Affiliations

  1. Department of Electrical and Computer Engineering, Kielce University of Technology, Al. 1000-lecia P.P. 7, 25-314, Kielce, Poland

    Filip Rudziński

Authors
  1. Filip Rudziński
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Correspondence to Filip Rudziński .

Editor information

Editors and Affiliations

  1. Częstochowa University of Technology, Częstochowa, Poland

    Leszek Rutkowski

  2. Częstochowa University of Technology, Częstochowa, Poland

    Marcin Korytkowski

  3. Częstochowa University of Technology, Częstochowa, Poland

    Rafał Scherer

  4. AGH University of Science and Technology, Kraków, Poland

    Ryszard Tadeusiewicz

  5. University of California, Berkeley, California, USA

    Lotfi A. Zadeh

  6. University of Louisville, Louisville, Kentucky, USA

    Jacek M. Zurada

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Rudziński, F. (2017). An Application of Generalized Strength Pareto Evolutionary Algorithm for Finding a Set of Non-Dominated Solutions with High-Spread and Well-Balanced Distribution in the Logistics Facility Location Problem. In: Rutkowski, L., Korytkowski, M., Scherer, R., Tadeusiewicz, R., Zadeh, L., Zurada, J. (eds) Artificial Intelligence and Soft Computing. ICAISC 2017. Lecture Notes in Computer Science(), vol 10245. Springer, Cham. https://doi.org/10.1007/978-3-319-59063-9_39

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  • DOI: https://doi.org/10.1007/978-3-319-59063-9_39

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-59062-2

  • Online ISBN: 978-3-319-59063-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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