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