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Multiobjective Landscape Analysis and the Generalized Assignment Problem

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Learning and Intelligent Optimization (LION 2007)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 5313))

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Abstract

The importance of tuning a search algorithm for the specific features of the target search space has been known for quite some time. However, when dealing with multiobjective problems, there are several twists on the conventional notions of fitness landscapes. Multiobjective optimization problems provide additional difficulties for those seeking to study the properties of the search space. However, the requirement of finding multiple candidate solutions to the problem also introduces new potentially exploitable structure. This paper provides a somewhat high-level overview of multiobjective search space and fitness landscape analysis and examines the impact of these features on the multiobjective generalized assignment problem.

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Authors and Affiliations

  1. University of Memphis, Memphis, TN, 38122, USA

    Deon Garrett & Dipankar Dasgupta

Authors
  1. Deon Garrett
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  2. Dipankar Dasgupta
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Editor information

Editors and Affiliations

  1. Dept. Computer Science, University of Bologna, Bologna, Italy

    Vittorio Maniezzo

  2. Università degli Studi di Trento, Trento, Italy

    Roberto Battiti

  3. Discrete Math and Complex Systems Department, Sandia National Laboratories, Albuquerque, New Mexico, USA

    Jean-Paul Watson

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Garrett, D., Dasgupta, D. (2008). Multiobjective Landscape Analysis and the Generalized Assignment Problem. In: Maniezzo, V., Battiti, R., Watson, JP. (eds) Learning and Intelligent Optimization. LION 2007. Lecture Notes in Computer Science, vol 5313. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-92695-5_9

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  • DOI: https://doi.org/10.1007/978-3-540-92695-5_9

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-92694-8

  • Online ISBN: 978-3-540-92695-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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