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A Simulated Annealing Approach to Communication Network Design

Author

Listed:
  • Marcus Randall

    (Bond University)

  • Graham McMahon

    (Bond University)

  • Stephen Sugden

    (Bond University)

Abstract

This paper explores the use of the meta-heuristic search algorithm Simulated Annealing for solving a minimum cost network synthesis problem. This problem is a common one in the design of telecommunication networks. The formulation we use models a number of practical problems with hop-limit, degree and capacity constraints. Emphasis is placed on a new approach that uses a knapsack polytope to select amongst a number of pre-computed traffic routes in order to synthesise the network. The advantage of this approach is that a subset of the best routes can be used instead of the whole set, thereby making the process of designing large networks practicable. Using simulated annealing, we solve moderately large networks (up to 30 nodes) efficiently.

Suggested Citation

  • Marcus Randall & Graham McMahon & Stephen Sugden, 2002. "A Simulated Annealing Approach to Communication Network Design," Journal of Combinatorial Optimization, Springer, vol. 6(1), pages 55-65, March.
    • Handle: RePEc:spr:jcomop:v:6:y:2002:i:1:d:10.1023_a:1013337324030
    DOI: 10.1023/A:1013337324030
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    References listed on IDEAS

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    1. Koulamas, C & Antony, SR & Jaen, R, 1994. "A survey of simulated annealing applications to operations research problems," Omega, Elsevier, vol. 22(1), pages 41-56, January.
    2. Connolly, David T., 1990. "An improved annealing scheme for the QAP," European Journal of Operational Research, Elsevier, vol. 46(1), pages 93-100, May.
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    Cited by:

    1. Dalila B. M. M. Fontes & S. Mahdi Homayouni & Mauricio G. C. Resende, 2022. "Job-shop scheduling-joint consideration of production, transport, and storage/retrieval systems," Journal of Combinatorial Optimization, Springer, vol. 44(2), pages 1284-1322, September.
    2. Konak, Abdullah, 2012. "Network design problem with relays: A genetic algorithm with a path-based crossover and a set covering formulation," European Journal of Operational Research, Elsevier, vol. 218(3), pages 829-837.
    3. Pinar Yildirim & Yanhao Wei & Christophe Bulte & Joy Lu, 2020. "Social network design for inducing effort," Quantitative Marketing and Economics (QME), Springer, vol. 18(4), pages 381-417, December.

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