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LAP Lambert Academic Publishing Optimization - The Bee's Way: A new swarm intelligence framework for unimodal, multimodal and dynamic optimization problems

Name: Optimization - The Bee's Way: A new swarm intelligence framework for unimodal, multimodal and dynamic optimization problems
Brand: LAP Lambert Academic Publishing
Price: 52.0 GBP
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Description

Swarm intelligence algorithms are taking the spotlight in the field of function optimization. In this book our attention centers on a new framework inspired from the food foraging behavior of honey bees. Utilizing the Particle Swarm Optimization (PSO) algorithm within this framework we have developed a novel algorithm called Honey Bee Foraging Particle Swarm Optimization (HBF-PSO). The HBF-PSO algorithm and its variants are suitable for solving multimodal and dynamic optimization problems. We focus on the niching and speciation capabilities of these algorithms which allow them to locate and track multiple peaks in multimodal and dynamic environments. The HBF-PSO algorithm performs a collective foraging for fitness in promising neighborhoods in combination with individual scouting searches in other areas. The strength of the algorithm lies in its continuous monitoring of the whole scouting and foraging process with dynamic relocation of the bees (solution/particles) if more promising regions are found. Those looking for a novel approach to function optimization utilizing the food foraging behavior of honey bees can benefit from the information presented in this book.

Product Specifications

Brand: LAP Lambert Academic Publishing
Format: paperback
ASIN: 3843358346
Category: Books > Subjects > Computing & Internet
Domain: Amazon UK
Release Date: 07 October 2010
Listed Since: 11 October 2010

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LAP Lambert Academic Publishing Optimization - The Bee's Way: A new swarm intelligence framework for unimodal, multimodal and dynamic optimization problems

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LAP Lambert Academic Publishing Optimization - The Bee's Way: A new swarm intelligence framework for unimodal, multimodal and dynamic optimization problems

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