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Genetic algorithm approach on multi-criteria minimum spanning tree problem

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  • Zhou, Gengui
  • Gen, Mitsuo

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  • 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.
    • Handle: RePEc:eee:ejores:v:114:y:1999:i:1:p:141-152
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    Citations

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    Cited by:

    1. 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.
    2. 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.
    3. Alonso, Sergio & Domínguez-Ríos, Miguel Ángel & Colebrook, Marcos & Sedeo-Noda, Antonio, 2009. "Optimality conditions in preference-based spanning tree problems," European Journal of Operational Research, Elsevier, vol. 198(1), pages 232-240, October.
    4. Cerrone, C. & Cerulli, R. & Raiconi, A., 2014. "Relations, models and a memetic approach for three degree-dependent spanning tree problems," European Journal of Operational Research, Elsevier, vol. 232(3), pages 442-453.
    5. Neumann, Frank, 2007. "Expected runtimes of a simple evolutionary algorithm for the multi-objective minimum spanning tree problem," European Journal of Operational Research, Elsevier, vol. 181(3), pages 1620-1629, September.
    6. Diabat, Ali & Kannan, Devika & Kaliyan, Mathiyazhagan & Svetinovic, Davor, 2013. "An optimization model for product returns using genetic algorithms and artificial immune system," Resources, Conservation & Recycling, Elsevier, vol. 74(C), pages 156-169.
    7. Min, Hokey & Jeung Ko, Hyun & Seong Ko, Chang, 2006. "A genetic algorithm approach to developing the multi-echelon reverse logistics network for product returns," Omega, Elsevier, vol. 34(1), pages 56-69, January.
    8. Pedro Correia & Luís Paquete & José Rui Figueira, 2021. "Finding multi-objective supported efficient spanning trees," Computational Optimization and Applications, Springer, vol. 78(2), pages 491-528, March.
    9. Lacour, Renaud, 2014. "Approches de résolution exacte et approchée en optimisation combinatoire multi-objectif, application au problème de l'arbre couvrant de poids minimal," Economics Thesis from University Paris Dauphine, Paris Dauphine University, number 123456789/14806 edited by Vanderpooten, Daniel.
    10. Dali Jiang & Haitao Li & Tinghong Yang & De Li, 2016. "Genetic algorithm for inventory positioning problem with general acyclic supply chain networks," European Journal of Industrial Engineering, Inderscience Enterprises Ltd, vol. 10(3), pages 367-384.
    11. I. F. C. Fernandes & E. F. G. Goldbarg & S. M. D. M. Maia & M. C. Goldbarg, 2020. "Empirical study of exact algorithms for the multi-objective spanning tree," Computational Optimization and Applications, Springer, vol. 75(2), pages 561-605, March.
    12. Selcen (Pamuk) Phelps & Murat Köksalan, 2003. "An Interactive Evolutionary Metaheuristic for Multiobjective Combinatorial Optimization," Management Science, INFORMS, vol. 49(12), pages 1726-1738, December.
    13. Mak, Brenda & Blanning, Robert & Ho, Susanna, 2006. "Genetic algorithms in logic tree decision modeling," European Journal of Operational Research, Elsevier, vol. 170(2), pages 597-612, April.
    14. Altannar Chinchuluun & Panos Pardalos, 2007. "A survey of recent developments in multiobjective optimization," Annals of Operations Research, Springer, vol. 154(1), pages 29-50, October.
    15. Medaglia, Andres L. & Fang, Shu-Cherng, 2003. "A genetic-based framework for solving (multi-criteria) weighted matching problems," European Journal of Operational Research, Elsevier, vol. 149(1), pages 77-101, August.
    16. Abraham P. Punnen & Ruonan Zhang, 2011. "Quadratic bottleneck problems," Naval Research Logistics (NRL), John Wiley & Sons, vol. 58(2), pages 153-164, March.
    17. Knowles, Joshua D. & Corne, David W., 2002. "Enumeration of Pareto optimal multi-criteria spanning trees - a proof of the incorrectness of Zhou and Gen's proposed algorithm," European Journal of Operational Research, Elsevier, vol. 143(3), pages 543-547, December.
    18. Clímaco, João C.N. & Eugénia Captivo, M. & Pascoal, Marta M.B., 2010. "On the bicriterion - minimal cost/minimal label - spanning tree problem," European Journal of Operational Research, Elsevier, vol. 204(2), pages 199-205, July.
    19. Juan Villegas & Fernando Palacios & Andrés Medaglia, 2006. "Solution methods for the bi-objective (cost-coverage) unconstrained facility location problem with an illustrative example," Annals of Operations Research, Springer, vol. 147(1), pages 109-141, October.
    20. G Zhou & M Gen, 2003. "A genetic algorithm approach on tree-like telecommunication network design problem," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 54(3), pages 248-254, March.
    21. Perny, Patrice & Spanjaard, Olivier, 2005. "A preference-based approach to spanning trees and shortest paths problems***," European Journal of Operational Research, Elsevier, vol. 162(3), pages 584-601, May.
    22. Zhou, Gengui & Min, Hokey & Gen, Mitsuo, 2003. "A genetic algorithm approach to the bi-criteria allocation of customers to warehouses," International Journal of Production Economics, Elsevier, vol. 86(1), pages 35-45, October.
    23. 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.
    24. Delorme, Xavier & Gandibleux, Xavier & Degoutin, Fabien, 2010. "Evolutionary, constructive and hybrid procedures for the bi-objective set packing problem," European Journal of Operational Research, Elsevier, vol. 204(2), pages 206-217, July.
    25. Wen, Hao & Sang, Song & Qiu, Chenhui & Du, Xiangrui & Zhu, Xiao & Shi, Qian, 2019. "A new optimization method of wind turbine airfoil performance based on Bessel equation and GABP artificial neural network," Energy, Elsevier, vol. 187(C).

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