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Modeling and solving the bi-objective minimum diameter-cost spanning tree problem

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  • Andréa Santos
  • Diego Lima
  • Dario Aloise

Abstract

The bi-objective minimum diameter-cost spanning tree problem (bi-MDCST) seeks spanning trees with minimum total cost and minimum diameter. The bi-objective version generalizes the well-known bounded diameter minimum spanning tree problem. The bi-MDCST is a NP-hard problem and models several practical applications in transportation and network design. We propose a bi-objective multiflow formulation for the problem and effective multi-objective metaheuristics: a multi-objective evolutionary algorithm and a fast nondominated sorting genetic algorithm. Some guidelines on how to optimize the problem whenever a priority order can be established between the two objectives are provided. In addition, we present bi-MDCST polynomial cases and theoretical bounds on the search space. Results are reported for four representative test sets. Copyright Springer Science+Business Media New York 2014

Suggested Citation

  • Andréa Santos & Diego Lima & Dario Aloise, 2014. "Modeling and solving the bi-objective minimum diameter-cost spanning tree problem," Journal of Global Optimization, Springer, vol. 60(2), pages 195-216, October.
    • Handle: RePEc:spr:jglopt:v:60:y:2014:i:2:p:195-216
    DOI: 10.1007/s10898-013-0124-4
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    References listed on IDEAS

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    1. Abilio Lucena & Celso Ribeiro & Andréa Santos, 2010. "A hybrid heuristic for the diameter constrained minimum spanning tree problem," Journal of Global Optimization, Springer, vol. 46(3), pages 363-381, March.
    2. Francis Sourd & Olivier Spanjaard, 2008. "A Multiobjective Branch-and-Bound Framework: Application to the Biobjective Spanning Tree Problem," INFORMS Journal on Computing, INFORMS, vol. 20(3), pages 472-484, August.
    3. Ramos, R. M. & Alonso, S. & Sicilia, J. & Gonzalez, C., 1998. "The problem of the optimal biobjective spanning tree," European Journal of Operational Research, Elsevier, vol. 111(3), pages 617-628, December.
    4. José Arroyo & Pedro Vieira & Dalessandro Vianna, 2008. "A GRASP algorithm for the multi-criteria minimum spanning tree problem," Annals of Operations Research, Springer, vol. 159(1), pages 125-133, March.
    5. Zhou, Gengui & Gen, Mitsuo, 1999. "Genetic algorithm approach on multi-criteria minimum spanning tree problem," European Journal of Operational Research, Elsevier, vol. 114(1), pages 141-152, April.
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    Cited by:

    1. Iago A. Carvalho & Amadeu A. Coco, 2023. "On solving bi-objective constrained minimum spanning tree problems," Journal of Global Optimization, Springer, vol. 87(1), pages 301-323, September.

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