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A heuristic method for solving the problem of partitioning graphs with supply and demand

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  • Raka Jovanovic
  • Abdelkader Bousselham
  • Stefan Voß

Abstract

In this paper we present a greedy algorithm for solving the problem of the maximum partitioning of graphs with supply and demand (MPGSD). The goal of the method is to solve the MPGSD for large graphs in a reasonable time limit. This is done by using a two stage greedy algorithm, with two corresponding types of heuristics. The solutions acquired in this way are improved by applying a computationally inexpensive, hill climbing like, greedy correction procedure. In our numeric experiments we analyze different heuristic functions for each stage of the greedy algorithm, and show that their performance is highly dependent on the properties of the specific instance. Our tests show that by exploring a relatively small number of solutions generated by combining different heuristic functions, and applying the proposed correction procedure we can find solutions within only a few percent of the optimal ones. Copyright Springer Science+Business Media New York 2015

Suggested Citation

  • Raka Jovanovic & Abdelkader Bousselham & Stefan Voß, 2015. "A heuristic method for solving the problem of partitioning graphs with supply and demand," Annals of Operations Research, Springer, vol. 235(1), pages 371-393, December.
    • Handle: RePEc:spr:annopr:v:235:y:2015:i:1:p:371-393:10.1007/s10479-015-1930-5
    DOI: 10.1007/s10479-015-1930-5
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    References listed on IDEAS

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    1. Scheuerer, Stephan & Wendolsky, Rolf, 2006. "A scatter search heuristic for the capacitated clustering problem," European Journal of Operational Research, Elsevier, vol. 169(2), pages 533-547, March.
    2. G. A. Croes, 1958. "A Method for Solving Traveling-Salesman Problems," Operations Research, INFORMS, vol. 6(6), pages 791-812, December.
    3. Philippe Galinier & Zied Boujbel & Michael Coutinho Fernandes, 2011. "An efficient memetic algorithm for the graph partitioning problem," Annals of Operations Research, Springer, vol. 191(1), pages 1-22, November.
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    1. Raka Jovanovic & Abdelkader Bousselham & Stefan Voß, 2018. "Partitioning of supply/demand graphs with capacity limitations: an ant colony approach," Journal of Combinatorial Optimization, Springer, vol. 35(1), pages 224-249, January.

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