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An adaptive heuristic to the bounded-diameter minimum spanning tree problem

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Abstract

Given a graph G and a bound d ≥ 2, the bounded-diameter minimum spanning tree problem seeks a spanning tree on G of minimum weight subject to the constraint that its diameter does not exceed d. This problem is NP-hard; several heuristics have been proposed to find near-optimal solutions to it in reasonable times. A decentralized learning automata-based algorithm creates spanning trees that honor the diameter constraint. The algorithm rewards a tree if it has the smallest weight found so far and penalizes it otherwise. As the algorithm proceeds, the choice probability of the tree converges to one; and the algorithm halts when this probability exceeds a predefined value. Experiments confirm the superiority of the algorithm over other heuristics in terms of both speed and solution quality.

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Authors and Affiliations

  1. Department of Computer Engineering, Arak Branch, Islamic Azad University, Arak, Iran

    Javad Akbari Torkestani

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  1. Javad Akbari Torkestani
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Akbari Torkestani, J. An adaptive heuristic to the bounded-diameter minimum spanning tree problem. Soft Comput 16, 1977–1988 (2012). https://doi.org/10.1007/s00500-012-0869-6

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