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Island models for cluster geometry optimization: how design options impact effectiveness and diversity

Designing island models is a challenging task for researchers. A number of decisions is required regarding the structure of the islands, how they are connected, how many individuals are migrated, which ones and how often. The impact of these choices is yet to be fully understood, specially since it...

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Published in:Journal of global optimization 2015-12, Vol.63 (4), p.677-707
Main Authors: Leitão, António, Pereira, Francisco Baptista, Machado, Penousal
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Language:English
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container_title Journal of global optimization
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creator Leitão, António
Pereira, Francisco Baptista
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description Designing island models is a challenging task for researchers. A number of decisions is required regarding the structure of the islands, how they are connected, how many individuals are migrated, which ones and how often. The impact of these choices is yet to be fully understood, specially since it may change between different problems and contexts. Cluster geometry optimization is a widely known and complex problem that provides a set of hard instances to assess and test optimization algorithms. The analysis presented in this paper reveals how design options for island models impact search effectiveness and population diversity, when seeking for the global optima of short-ranged Morse clusters. These outcomes support the definition of a robust and scalable island-based framework for cluster geometry optimization problems.
doi_str_mv 10.1007/s10898-015-0302-7
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subjects Algorithms
Analysis
Atoms & subatomic particles
Basins
Clusters
Computer Science
Design
Design engineering
Geometry
Impact analysis
Islands
Mathematical optimization
Mathematics
Mathematics and Statistics
Operations Research/Decision Theory
Optimization
Optimization algorithms
Population
Real Functions
Searching
Studies
Tasks
Test systems
title Island models for cluster geometry optimization: how design options impact effectiveness and diversity
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