Titlebook: Innovations in Swarm Intelligence; Chee Peng Lim,Lakhmi C. Jain,Satchidananda Dehuri Book 2009 Springer-Verlag Berlin Heidelberg 2009 Desi

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A Review of Particle Swarm Optimization Methods Used for Multimodal Optimization, of optimization tasks [1,2]. However, its use in multimodal optimization (i.e., single-objective optimization problems having multiple optima) has been relatively scarce..In this chapter, we will review the most representative PSO-based approaches that have been proposed to deal with multimodal opt

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Bee Colony Optimization (BCO),timization (BCO) metaheuristic has been introduced fairly recently as a new direction in the field of Swarm Intelligence. Artificial bees represent agents, which collaboratively solve complex combinatorial optimization problem. The chapter presents a classification and analysis of the results achiev

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Glowworm Swarm Optimization for Searching Higher Dimensional Spaces,orithm, which was recently proposed for simultaneous capture of multiple optima of multimodal functions. Tests are performed on a set of three benchmark functions and the . is used as an index to analyze GSO’s performance as a function of dimension number. Results reported from tests conducted up to

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Bricklayer

A Multi-resolution GA-PSO Layered Encoding Cascade Optimization Model,ch space, and resolution affects the accuracy and performance of an optimization model. This article presents a genetic algorithm and particle swarm based cascade multi-resolution optimization model, and it is known as GA-PSO LECO. GA and PSO are combined in this research to integrate random as well

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Factual

Particle Swarm Optimization for Optimal Operational Planning of Energy Plants,nergy plants, which are formulated as Mixed-Intger Nonlinear Problems (MINLPs). The three methods are compared using typical energy plant operational planning problems. We have been developed an optimal operational planning and control system of energy plants using PSO (called FeTOP). FeTOP has been

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