Multi-population inflationary differential evolution algorithm with adaptive local restart

Marilena Di Carlo; Massimiliano Vasile; Edmondo Minisci

doi:10.1109/CEC.2015.7256950

Multi-population inflationary differential evolution algorithm with adaptive local restart

Marilena Di Carlo, Massimiliano Vasile, Edmondo Minisci

Mechanical And Aerospace Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution book

3 Citations (Scopus)

207 Downloads (Pure)

Abstract

In this paper a Multi-Population Inflationary Differential Evolution algorithm with Adaptive Local Restart is presented and extensively tested over more than fifty test functions from the CEC 2005, CEC 2011 and CEC 2014 competitions. The algorithm combines a multi-population adaptive Differential Evolution with local search and local and global restart procedures. The proposed algorithm implements a simple but effective mechanism to avoid multiple detections of the same local minima. The novel mechanism allows the algorithm to decide whether to start or not a local search. The local restart of the population, which follows the local search, is, therefore, automatically adapted.

Original language	English
Title of host publication	2015 IEEE Congress on Evolutionary Computation, CEC 2015 - Proceedings
Pages	632-639
Number of pages	8
DOIs	https://doi.org/10.1109/CEC.2015.7256950
Publication status	Published - 10 Sep 2015
Event	IEEE Congress on Evolutionary Computation, CEC 2015 - Sendai, Japan Duration: 25 May 2015 → 28 May 2015

Conference

Conference	IEEE Congress on Evolutionary Computation, CEC 2015
Country/Territory	Japan
City	Sendai
Period	25/05/15 → 28/05/15

Keywords

global optimization
differential evolution
multi-population algorithm
adaptive algorithm

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10.1109/CEC.2015.7256950

Di-Carlo-etal-CEC2015-Multi-population-inflationary-differential-evolution-algorithm-adaptive-local-restartAccepted author manuscript, 126 KB

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title = "Multi-population inflationary differential evolution algorithm with adaptive local restart",

abstract = "In this paper a Multi-Population Inflationary Differential Evolution algorithm with Adaptive Local Restart is presented and extensively tested over more than fifty test functions from the CEC 2005, CEC 2011 and CEC 2014 competitions. The algorithm combines a multi-population adaptive Differential Evolution with local search and local and global restart procedures. The proposed algorithm implements a simple but effective mechanism to avoid multiple detections of the same local minima. The novel mechanism allows the algorithm to decide whether to start or not a local search. The local restart of the population, which follows the local search, is, therefore, automatically adapted.",

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AU - Di Carlo, Marilena

AU - Vasile, Massimiliano

AU - Minisci, Edmondo

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N2 - In this paper a Multi-Population Inflationary Differential Evolution algorithm with Adaptive Local Restart is presented and extensively tested over more than fifty test functions from the CEC 2005, CEC 2011 and CEC 2014 competitions. The algorithm combines a multi-population adaptive Differential Evolution with local search and local and global restart procedures. The proposed algorithm implements a simple but effective mechanism to avoid multiple detections of the same local minima. The novel mechanism allows the algorithm to decide whether to start or not a local search. The local restart of the population, which follows the local search, is, therefore, automatically adapted.

AB - In this paper a Multi-Population Inflationary Differential Evolution algorithm with Adaptive Local Restart is presented and extensively tested over more than fifty test functions from the CEC 2005, CEC 2011 and CEC 2014 competitions. The algorithm combines a multi-population adaptive Differential Evolution with local search and local and global restart procedures. The proposed algorithm implements a simple but effective mechanism to avoid multiple detections of the same local minima. The novel mechanism allows the algorithm to decide whether to start or not a local search. The local restart of the population, which follows the local search, is, therefore, automatically adapted.

KW - global optimization

KW - differential evolution

KW - multi-population algorithm

KW - adaptive algorithm

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U2 - 10.1109/CEC.2015.7256950

DO - 10.1109/CEC.2015.7256950

M3 - Conference contribution book

AN - SCOPUS:84963542820

SN - 9781479974924

SP - 632

EP - 639

BT - 2015 IEEE Congress on Evolutionary Computation, CEC 2015 - Proceedings

T2 - IEEE Congress on Evolutionary Computation, CEC 2015

Y2 - 25 May 2015 through 28 May 2015

ER -

Multi-population inflationary differential evolution algorithm with adaptive local restart

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Adaptive multi-population inflationary differential evolution

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