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Recent approaches to global optimization problems through Particle Swarm Optimization
A Composite PSO, in which the heuristic parameters of PSO are controlled by a Differential Evolution algorithm during the optimization, is described, and results for many well-known and widely used test functions are given. Expand
UPSO: A Unified Particle Swarm Optimization Scheme
Particle swarm optimization method in multiobjective problems
Critical aspects of the VEGA approach for Multiobjective Optimization using Genetic Algorithms are adapted to the PSO framework in order to develop a multi-swarm PSO that can cope effectively with MO problems. Expand
Particle Swarm Optimization and Intelligence: Advances and Applications
Particle Swarm Optimization and Intelligence: Advances and Applications examines modern intelligent optimization algorithms proven as very efficient in applications from various scientific andExpand
On the computation of all global minimizers through particle swarm optimization
The approaches include transformations of the objective function through the recently proposed deflection and stretching techniques, as well as a repulsion source at each detected minimizer, resulting in an efficient algorithm which has the ability to avoid previously detected solutions and, thus, detect all global minimizers of a function. Expand
Particle Swarm Optimization Method for Constrained Optimization Problems
The performance of the Particle Swarm Optimization method in coping with Constrained Optimization problems is investigated and results are compared with those obtained through other evolutionary algorithms, such as Evolution Strategies and Genetic Algorithms. Expand
Unified Particle Swarm Optimization for Solving Constrained Engineering Optimization Problems
A penalty function approach is employed and the algorithm is modified to preserve feasibility of the encountered solutions to investigate the performance of the recently proposed Unified Particle Swarm Optimization method on constrained engineering optimization problems. Expand
Particle swarm optimization for integer programming
Three variants of PSO are compared with the widely used branch and bound technique, on several integer programming test problems and results indicate that PSO handles efficiently such problems, and in most cases it outperforms the branch and Bound technique. Expand
Parallel differential evolution
Experimental results indicate that the extent of information exchange among subpopulations assigned to different processor nodes, bears a significant impact on the performance of the algorithm. Expand
Enhancing Differential Evolution Utilizing Proximity-Based Mutation Operators
This paper incorporates a novel framework based on the proximity characteristics among the individual solutions as they evolve, which incorporates information of neighboring individuals in an attempt to efficiently guide the evolution of the population toward the global optimum. Expand