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Interleaving Innovization with Evolutionary Multi-Objective Optimization in Production System Simulation for Faster Convergence Read chapter Read first chapter

2013 | OriginalPaper | Chapter

Oversized Populations and Cooperative Selection: Dealing with Massive Resources in Parallel Infrastructures

Authors : Juan Luis Jiménez Laredo, Bernabe Dorronsoro, Carlos Fernandes, Juan Julian Merelo, Pascal Bouvry

Published in: Learning and Intelligent Optimization

Publisher: Springer Berlin Heidelberg

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Abstract

This paper proposes a new selection scheme for Evolutionary Algorithms (EAs) based on altruistic cooperation between individuals. Cooperation takes place every time an individual undergoes selection: the individual decreases its own fitness in order to improve the mating chances of worse individuals. On the one hand, the selection scheme guarantees that the genetic material of fitter individuals passes to subsequent generations as to decrease their fitnesses individuals have to be firstly selected. On the other hand, the scheme restricts the number of times an individual can be selected not to take over the entire population. We conduct an empirical study for a parallel EA version where cooperative selection scheme is shown to outperform binary tournament: both selection schemes yield the same qualities of solutions but cooperative selection always improves the times to solutions.

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previous chapter Practically Desirable Solutions Search on Multi-Objective Optimization
next chapter Effects of Population Size on Selection and Scalability in Evolutionary Many-Objective Optimization
Footnotes
1
We follow here the selectorecombinative approach of Lobo and Lima [7] for studying the scalability of the population size.
 
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Metadata
Title
Oversized Populations and Cooperative Selection: Dealing with Massive Resources in Parallel Infrastructures
Authors
Juan Luis Jiménez Laredo
Bernabe Dorronsoro
Carlos Fernandes
Juan Julian Merelo
Pascal Bouvry
Copyright Year
2013
Publisher
Springer Berlin Heidelberg
Book
Learning and Intelligent Optimization

Print ISBN: 978-3-642-44972-7

Electronic ISBN: 978-3-642-44973-4

Copyright Year: 2013

DOI
https://doi.org/10.1007/978-3-642-44973-4_47

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