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Particle Swarm Optimization (PSO) belongs to a class of algorithms inspired by natural social intelligent behaviors, called Swarm Intelligence (SI). PSO has been successfully applied to solve continuous optimization problems, however, its potential in discrete problems has not been sufficiently explored. Recent works have proposed hybridization of PSO using local search and Path relinking algorithms...
Clustering analysis based on ant swarm intelligence is discussed. As traditional clustering algorithm is easy to obtain local optimum, it uses ant swarm intelligence to obtain global search. It improves the clustering by locating the objects in a cluster with the probability, which is updated by the pheromone, while the rule of updating pheromone is according to total within cluster variance. According...
Traveling salesman problem (TSP) is one of the most famous NP-hard problems, which has wide application background. Ant colony optimization (ACO) is a nature-inspired algorithm and taken as one of the high performance computing methods for TSP. Classical ACO algorithm like ant colony system (ACS) cannot solve TSP very well. The present paper proposes an ACO algorithm with multi-direction searching...
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