According to the intelligent behavior of social population, the centroid of the individual best of particle swarm is firstly introduced in particle swarm optimization (PSO) model to enhance inter-particle cooperation and information sharing capabilities, then combining the mechanism of population migration algorithm (PMA), a novel PSO algorithm with adaptive space mutation (PMCPSO) is proposed ...

Image registration is a useful technique for medical diagnosis and treatment. However,using basic genetic algorithm as similarity metric in medical image registration has some shortcomings,such as low efficiency and premature convergence that may lead to fail in medical image registration. This paper aims to provide an improved genetic algorithm on which such problems could be settled.Operation...

Image segmentation plays a crucial role in many medical applications. The threshold based medical image segmentation approach is the most common and effective method for medical image segmentation, but it has some shortcomings such as high complexity, poor real time capability and premature convergence, etc. To address above issues, an improved evolution strategies is proposed to use for medica...

Particle Swarm Optimization (PSO) is a bio-inspired evolutionary meta-heuristic that simulates the social behaviour observed in groups of biological individuals [4]. In standard PSO, the particle swarm is often attracted by sub-optimal solutions when solving complex multimodal problems, causing premature convergence of the algorithm and swarm stagnation [5]. Once particles have converged premat...

Particle Swarm Optimization (PSO) is a biologically inspired computational search and optimization method based on the social behaviors of birds flocking or fish schooling. Although PSO is represented in solving many well-known numerical test problems, but it suffers from the premature convergence. A number of basic variations have been developed due to solve the premature convergence problem a...

Genetic algorithms are a population-based Meta heuristics. They have been successfully applied to many optimization problems. However, premature convergence is an inherent characteristic of such classical genetic algorithms that makes them incapable of searching numerous solutions of the problem domain. A memetic algorithm is an extension of the traditional genetic algorithm. It uses a local se...

This paper presents a modification of the particle swarm optimization algorithm (PSO) intended to combat the problem of premature convergence observed in many applications of PSO. In the new algorithm, each particle is attracted towards the best previous positions visited by its neighbors, in addition to the other aspects of particle dynamics in PSO. This is accomplished by using the ratio of t...

Premature convergence is one of the important issues while using Genetic Programming for data modeling. It can be avoided by improving population diversity. Intelligent genetic operators can help to improve the population diversity. Crossover is an important operator in Genetic Programming. So, we have analyzed number of intelligent crossover operators and proposed an algorithm with the modific...