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New Metaheuristic Approaches For The Leaf-Constrained Minimum Spanning Tree Problem

Author

Listed:
  • ALOK SINGH

    (Department of Computer and Information Sciences, School of Mathematics and Computer/Information Sciences, University of Hyderabad, Hyderabad – 500046, Andhra Pradesh, India)

  • ANURAG SINGH BAGHEL

    (Department of Electronics and Communication, Banasthali Vidyapith Jaipur Campus, Sarojini Marg, Jaipur – 302001, Rajasthan, India)

Abstract

Given an undirected, connected, weighted graph, the leaf-constrained minimum spanning tree (LCMST) problem seeks a spanning tree of the graph with smallest weight among all spanning trees of the graph, which contains at leastlleaves. In this paper we have proposed two new metaheuristic approaches for the LCMST problem. One is an ant-colony optimization (ACO) algorithm, whereas the other is a tabu search based algorithm. Similar to a previously proposed genetic algorithm, these metaheuristic approaches also use the subset coding that represents a leaf-constrained spanning tree by the set of its interior vertices. Our new approaches perform well in comparison with two best heuristics reported in the literature for the problem — the subset-coded genetic algorithm and a greedy heuristic.

Suggested Citation

  • Alok Singh & Anurag Singh Baghel, 2008. "New Metaheuristic Approaches For The Leaf-Constrained Minimum Spanning Tree Problem," Asia-Pacific Journal of Operational Research (APJOR), World Scientific Publishing Co. Pte. Ltd., vol. 25(04), pages 575-589.
    • Handle: RePEc:wsi:apjorx:v:25:y:2008:i:04:n:s0217595908001870
    DOI: 10.1142/S0217595908001870
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