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International Conference on Evolutionary Multi-Criterion Optimization

EMO 2005: Evolutionary Multi-Criterion Optimization pp 797–810Cite as

Finding Pareto-Optimal Set by Merging Attractors for a Bi-objective Traveling Salesmen Problem

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Part of the Lecture Notes in Computer Science book series (LNTCS,volume 3410)

Abstract

This paper presents a new search procedure to tackle multi-objective traveling salesman problem (TSP). This procedure constructs the solution at-tractor for each of the objectives respectively. Each attractor contains the best solutions found for the corresponding objective. Then, these attractors are merged to find the Pareto-optimal solutions. The goal of this procedure is not only to generate a set of Pareto-optimal solutions, but also to provide the infor-mation about these solutions that will allow a decision-maker to choose a good compromise solution.

Keywords

  • Local Search
  • Multiobjective Optimization
  • Travel Salesman Problem
  • Travel Salesman Problem
  • Local Search Algorithm

These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Author information

Authors and Affiliations

  1. School of Management, University of Michigan-Flint, 303 East Kearsley Street, Flint, Michigan, 48502, U.S.A.

    Weiqi Li

Authors
  1. Weiqi Li
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Editor information

Editors and Affiliations

  1. Departamento de Computación, CINVESTAV-IPN (Evolutionary Computation Group), 07300, México, D.F., México

    Carlos A. Coello Coello

  2. Centro de Investigación en Matemáticas (CIMAT), A.P. 402, Guanajuato, 36000, Mexico

    Arturo Hernández Aguirre

  3. Computer Engineering and Networks Laboratory, ETH, Zurich, Switzerland

    Eckart Zitzler

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Li, W. (2005). Finding Pareto-Optimal Set by Merging Attractors for a Bi-objective Traveling Salesmen Problem . In: Coello Coello, C.A., Hernández Aguirre, A., Zitzler, E. (eds) Evolutionary Multi-Criterion Optimization. EMO 2005. Lecture Notes in Computer Science, vol 3410. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-31880-4_55

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  • DOI: https://doi.org/10.1007/978-3-540-31880-4_55

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-24983-2

  • Online ISBN: 978-3-540-31880-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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