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Practically Desirable Solutions Search on Multi-Objective Optimization

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Book cover Learning and Intelligent Optimization (LION 2013)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 7997))

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Abstract

This work investigates a method to search practically desirable solutions expanding the objective space with additional fitness functions associated to particular decision variables. The aim is to find solutions around preferred values of the chosen variables while searching for optimal solutions in the original objective space. Solutions to be practically desirable are constrained to be within a certain distance from the instantaneous Pareto optimal set computed in the original objective space. Our experimental results show that the proposed method can effectively find practically desirable solutions.

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References

  1. Coello, C., Van Veldhuizen, D., Lamont, G.: Evolutionary Algorithms for Solving Multi-Objective Problems. Kluwer Academic, Boston (2002)

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Authors and Affiliations

  1. Faculty of Engineering, Shinshu University, 4-17-1 Wakasato, Nagano, 380-8553, Japan

    Natsuki Kusuno, Hernán Aguirre & Kiyoshi Tanaka

  2. R&D Center, The Yokohama Rubber Co. Ltd., 2-1 Oiwake, Hiratsuka, Kanagawa, 254-8601, Japan

    Masataka Koishi

Authors
  1. Natsuki Kusuno
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  2. Hernán Aguirre
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  3. Kiyoshi Tanaka
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  4. Masataka Koishi
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Corresponding author

Correspondence to Masataka Koishi .

Editor information

Editors and Affiliations

  1. Università Catania Dipto. Matematica e Informatica, Catania, Italy

    Giuseppe Nicosia

  2. Industrial & Systems Engineering, University of Florida, Gainesville, Florida, USA

    Panos Pardalos

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© 2013 Springer-Verlag Berlin Heidelberg

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Kusuno, N., Aguirre, H., Tanaka, K., Koishi, M. (2013). Practically Desirable Solutions Search on Multi-Objective Optimization. In: Nicosia, G., Pardalos, P. (eds) Learning and Intelligent Optimization. LION 2013. Lecture Notes in Computer Science(), vol 7997. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-44973-4_46

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  • DOI: https://doi.org/10.1007/978-3-642-44973-4_46

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-44972-7

  • Online ISBN: 978-3-642-44973-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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