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Multiobjective Quadratic Assignment Problem Solved by an Explicit Building Block Search Algorithm – MOMGA-IIa

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Evolutionary Computation in Combinatorial Optimization (EvoCOP 2005)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 3448))

Abstract

The multi-objective quadratic assignment problem (mQAP) is an non-deterministic polynomial-time complete (NPC) problem with many real-world applications. The application addressed in this paper is the minimization of communication flows in a heterogenous mix of Organic Air Vehicles (OAV). A multi-objective approach to solving the general mQAP for this OAV application is developed. The combinatoric nature of this problem calls for a stochastic search algorithm; moreover, two linkage learning algorithms, the multi-objective fast messy genetic algorithm (MOMGA-II) and MOMGA-IIa, are compared. Twenty-three different problem instances having three different sizes (10, 20, and 30) plus two and three objectives are solved. Results indicate that the MOMGA-IIa resolves all pareto optimal points for problem instances < 20.

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Authors and Affiliations

  1. Department of Electrical Engineering, Graduate School of Engineering & Management, Air Force Institute of Technology, WPAFB (Dayton), OH, 45433, USA

    Richard O. Day & Gary B. Lamont

Authors
  1. Richard O. Day
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  2. Gary B. Lamont
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Editor information

Editors and Affiliations

  1. Institute of Computer Graphics and Algorithms, Vienna University of Technology, Favoritenstraße 9–11/1861, 1040, Vienna, Austria

    Günther R. Raidl

  2. SAP AG, Neurottstr. 16, P.O. Box, Walldorf, Germany

    Jens Gottlieb

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© 2005 Springer-Verlag Berlin Heidelberg

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Day, R.O., Lamont, G.B. (2005). Multiobjective Quadratic Assignment Problem Solved by an Explicit Building Block Search Algorithm – MOMGA-IIa. In: Raidl, G.R., Gottlieb, J. (eds) Evolutionary Computation in Combinatorial Optimization. EvoCOP 2005. Lecture Notes in Computer Science, vol 3448. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-31996-2_9

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  • DOI: https://doi.org/10.1007/978-3-540-31996-2_9

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-25337-2

  • Online ISBN: 978-3-540-31996-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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