An image clustering method that is based on the particle swarm optimizer (PSO) is developed in this paper. The algorithm finds the centroids of a user specified number of clusters, where each cluster groups together similar image primitives. To illustrate its wide applicability, the proposed image classifier has been applied to synthetic, MRI and satellite images. Experimental results show that...

In this paper, we present the interaction and co-evolutionary process between genetic algorithm-based agent (GA-based agent) and particle swarm optimization-based agent (PSO-based agent) in the bargaining game. Experimental results show that a PSO-based agent evolves a greedy agent even though the deal can't be accomplished but a GA-based one evolves a passive agent to accomplish a deal. Becaus...

The reactive power planning and dispatch problems have been solved using Genetic algorithm (GA), Differential evolution (DE) and Particle Swarm Optimization (PSO) technique in order to have a comparative study on the performance of these algorithms. It has been found that Differential evolution performs best followed by the Particle swarm optimization. Both DE and PSO can perform well even with...

Artificial bee colony (ABC) algorithm invented recently by Karaboga is a biological-inspired optimization algorithm, which has been shown to be competitive with some conventional biological-inspired algorithms, such as genetic algorithm (GA), differential evolution (DE) and particle swarm optimization (PSO). However, there is still an insufficiency in ABC algorithm regarding its solution search...

This paper proposes a motion compensation method to compensate for the inter-pulse phase errors caused by the target movement in stepped-frequency ISAR imaging. For this purpose, genetic algorithm, particle swarm optimization (PSO) and PSO with an island model (PSOI) were applied in the proposed procedure. Simulation results using point scatterers and measured data show that PSOI is the most ef...

In this paper a CAD (Computer Aided Diagnosis) system is proposed to optimize the feature set using hybrid of Particle Swarm Optimization (PSO) and Genetic Algorithm (GA) technique called Genetical Swarm Optimization (GSO) in Digital Mammogram. Even though PSO is a good optimization technique, it may be trapped in local minima and may prematurely converge. So, the genetic operators are used in ...

With rapid economic and demographic growth, traffic conditions in medium large cities are becoming extremely congested. Numerous metropolitan management organizations hope to promote the coordination of urban development by formulating improving strategies. The effectiveness these solutions depends largely on an accurate assessment distribution hotspots (centers activity). In recent years, many...

The traveling salesman problem (TSP) is the problem of finding the shortest tour through all the nodes that a salesman has to visit. The TSP is probably the most famous and extensively studied problem in the field of combinatorial optimization. Because this problem is an NP-hard problem, practical large-scale instances cannot be solved by exact algorithms within acceptable computational times. ...

The traveling salesman problem (TSP) is the problem of finding the shortest tour through all the nodes that a salesman has to visit. The TSP is probably the most famous and extensively studied problem in the field of combinatorial optimization. Because this problem is an NP-hard problem, practical large-scale instances cannot be solved by exact algorithms within acceptable computational times. ...