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A fuzzy particle swarm optimization algorithm for computer communication network topology design

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Abstract

Particle swarm optimization (PSO) is a powerful optimization technique that has been applied to solve a number of complex optimization problems. One such optimization problem is topology design of distributed local area networks (DLANs). The problem is defined as a multi-objective optimization problem requiring simultaneous optimization of monetary cost, average network delay, hop count between communicating nodes, and reliability under a set of constraints. This paper presents a multi-objective particle swarm optimization algorithm to efficiently solve the DLAN topology design problem. Fuzzy logic is incorporated in the PSO algorithm to handle the multi-objective nature of the problem. Specifically, a recently proposed fuzzy aggregation operator, namely the unified And-Or operator (Khan and Engelbrecht in Inf. Sci. 177: 2692–2711, 2007), is used to aggregate the objectives. The proposed fuzzy PSO (FPSO) algorithm is empirically evaluated through a preliminary sensitivity analysis of the PSO parameters. FPSO is also compared with fuzzy simulated annealing and fuzzy ant colony optimization algorithms. Results suggest that the fuzzy PSO is a suitable algorithm for solving the DLAN topology design problem.

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Authors and Affiliations

  1. Computer Engineering Department, King Fahd University of Petroleum & Minerals, Dhahran, 31261, Saudi Arabia

    Salman A. Khan

  2. Department of Computer Science, University of Pretoria, Pretoria, 0002, South Africa

    Andries P. Engelbrecht

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  1. Salman A. Khan
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  2. Andries P. Engelbrecht
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Correspondence to Salman A. Khan.

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Khan, S.A., Engelbrecht, A.P. A fuzzy particle swarm optimization algorithm for computer communication network topology design. Appl Intell 36, 161–177 (2012). https://doi.org/10.1007/s10489-010-0251-2

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