Comparison of PSO and GA for K-Node Set Reliability Optimization of a Distributed System
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Abstract
Particle Swarm Optimization (PSO), as a novel evolutionary computing technique, has succeeded in many continuous problems, but quite a little research on discrete problem especially combinatorial optimization problem has been reported. In this paper, a discrete PSO algorithm is proposed to solve a typical combinatorial optimization problem: K-Node Set Reliability (KNR) optimization of a distributed computing system (DCS) which is a well-known NP-hard problem is presented. It computes the reliability of a subset of network nodes of a DCS such that the reliability is maximized and specified capacity constraint is satisfied. The feasibility of the proposed algorithm is demonstrated on 8 nodes 11 links DCS topology. The test results are compared with those obtained by the genetic algorithm (GA) method in terms of solution quality and convergence characteristics. Experimental study shows that the proposed PSO algorithm can achieve good results.
