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International Conference on Parallel Problem Solving from Nature

PPSN 2010: Parallel Problem Solving from Nature, PPSN XI pp 31–40Cite as

Improved Dynamic Lexicographic Ordering for Multi-Objective Optimisation

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Part of the Lecture Notes in Computer Science book series (LNTCS,volume 6239)

Abstract

There is a variety of methods for ranking objectives in multi-objective optimization and some are difficult to define because they require information a priori (e.g. establishing weights in a weighted approach or setting the ordering in a lexicographic approach). In many-objective optimization problems, those methods may exhibit poor diversification and intensification performance. We propose the Dynamic Lexicographic Approach (DLA). In this ranking method, the priorities are not fixed, but they change throughout the search process. As a result, the search process is less liable to get stuck in local optima and therefore, DLA offers a wider exploration in the objective space. In this work, DLA is compared to Pareto dominance and lexicographic ordering as ranking methods within a Discrete Particle Swarm Optimization algorithm tackling the Vehicle Routing Problem with Time Windows.

Keywords

  • Multi-objective Optimization
  • Swarm Optimization
  • Combinatorial Optimization
  • Vehicle Routing Problem

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Author information

Authors and Affiliations

  1. ASAP Research Group, School of Computer Science, University of Nottingham, UK

    Juan Castro-Gutierrez & Dario Landa-Silva

  2. Dpto. de Estadística, I.O. y Computación, Universidad de La Laguna, Spain

    José Moreno Pérez

Authors
  1. Juan Castro-Gutierrez
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  2. Dario Landa-Silva
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  3. José Moreno Pérez
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Editor information

Editors and Affiliations

  1. Faculty of Electrical Engineering, Automatics, Computer Science and Electronics, Department of ComputerScience, AGH University of Science and Technology, Mickiewicza 30, 30-059, Kraków, Poland

    Robert Schaefer

  2. Departamento de Lenguajes y Ciencias de la Computación, ETSI Informática, Universidad de Málaga, Campus Teatinos, 29071, Málaga, Spain

    Carlos Cotta

  3. Department of Mathematics and Computer Science, University of Bielsko-Biala, Willowa 2, 43-309, Bielsko-Biala, Poland

    Joanna Kołodziej

  4. Fakultät für Informatik, Technische Universität Dortmund, 44221, Dortmund, Germany

    Günter Rudolph

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Castro-Gutierrez, J., Landa-Silva, D., Pérez, J.M. (2010). Improved Dynamic Lexicographic Ordering for Multi-Objective Optimisation. In: Schaefer, R., Cotta, C., Kołodziej, J., Rudolph, G. (eds) Parallel Problem Solving from Nature, PPSN XI. PPSN 2010. Lecture Notes in Computer Science, vol 6239. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-15871-1_4

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  • DOI: https://doi.org/10.1007/978-3-642-15871-1_4

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-15870-4

  • Online ISBN: 978-3-642-15871-1

  • eBook Packages: Computer ScienceComputer Science (R0)