The aim of this work is to introduce an effective tool in order to help the EM designer to select the best optimization algorithm through an easy-to-manage classification of Evolutionary Algorithms. In fact, choosing the best tool for an application could be really di cult, especially for a user not aware of optimization theory. Here we propose a general analysis for EAs, highlighting their block-structure and classifying them through some objective (non-qualitative) parameters.

General structure-based classification of Optimization Algorithms for an objective comparison

NICCOLAI, ALESSANDRO;GONANO, CARLO ANDREA;GRIMACCIA, FRANCESCO;MUSSETTA, MARCO;ZICH, RICCARDO
2015

Abstract

The aim of this work is to introduce an effective tool in order to help the EM designer to select the best optimization algorithm through an easy-to-manage classification of Evolutionary Algorithms. In fact, choosing the best tool for an application could be really di cult, especially for a user not aware of optimization theory. Here we propose a general analysis for EAs, highlighting their block-structure and classifying them through some objective (non-qualitative) parameters.
Proceedings of the 2015 International Conference on Electromagnetics in Advanced Applications, ICEAA 2015
9781479978069
9781479978069
Algorithm design and analysis; Genetic algorithms; Optimization; Planar arrays; Sensitivity; Sociology; Statistics; Electrical and Electronic Engineering; Instrumentation; Radiation
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11311/985997
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