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Constraint Optimization Techniques for Exact Multi-Objective Optimization

In: Multiobjective Programming and Goal Programming

Author

Listed:
  • Rollon Emma

    (Universitat Politècnica de Catalunya, Jordi Girona 1-3)

  • Larrosa Javier

    (Universitat Politècnica de Catalunya, Jordi Girona 1-3)

Abstract

MultiObjective Branch and Bound search has not been widely studied in the multiobjective context. The main reason is the lack of general approximation algorithms to compute lower bound sets. However, many lower bound techniques has been proposed for mono-objective optimization in the constraint programming field. In particular, Mini-Bucket Elimination (MBE) is a powerful mechanism for lower bound computation. Recently, MBE has been extended to multi-objective optimization problems. The new algorithm, called MO-MBE, computes a lower bound set of the efficient frontier of the problem. We show how to embed MO-MBE in a multi-objective branch and bound search, and we empirically demonstrate the performance of the new approach in two different domains.

Suggested Citation

  • Rollon Emma & Larrosa Javier, 2009. "Constraint Optimization Techniques for Exact Multi-Objective Optimization," Lecture Notes in Economics and Mathematical Systems, in: Vincent Barichard & Matthias Ehrgott & Xavier Gandibleux & Vincent T'Kindt (ed.), Multiobjective Programming and Goal Programming, pages 89-98, Springer.
    • Handle: RePEc:spr:lnechp:978-3-540-85646-7_9
    DOI: 10.1007/978-3-540-85646-7_9
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    Cited by:

    1. Shuli Hu & Xiaoli Wu & Huan Liu & Yiyuan Wang & Ruizhi Li & Minghao Yin, 2019. "Multi-Objective Neighborhood Search Algorithm Based on Decomposition for Multi-Objective Minimum Weighted Vertex Cover Problem," Sustainability, MDPI, vol. 11(13), pages 1-21, July.

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