Adaptive inflationary differential evolution

Edmondo Minisci; Massimiliano Vasile

doi:10.1109/CEC.2014.6900587

Adaptive inflationary differential evolution

Edmondo Minisci^*, Massimiliano Vasile

^*Corresponding author for this work

Research output: Contribution to conference › Paper

11 Citations (Scopus)

117 Downloads (Pure)

Abstract

In this paper, an adaptive version of Inflationary Differential Evolution is presented and tested on a set of real case problems taken from the CEC2011 competition on realworld applications. Inflationary Differential Evolution extends standard Differential Evolution with both local and global restart procedures. The proposed adaptive algorithm utilizes a probabilistic kernel based approach to automatically adapt the values of both the crossover and step parameters. In addition the paper presents a sensitivity analysis on the values of the parameters controlling the local restart mechanism and their impact on the solution of one of the hardest problems in the CEC2011 test set.

Original language	English
Pages	1792-1799
Number of pages	8
DOIs	https://doi.org/10.1109/CEC.2014.6900587
Publication status	Published - 6 Jul 2014
Event	CEC 2014: IEEE Conference on Evolutionary computation - Beijing, China Duration: 6 Jul 2014 → 11 Jul 2014 http://www.ieee-wcci2014.org/

Conference

Conference	CEC 2014
Country/Territory	China
City	Beijing
Period	6/07/14 → 11/07/14
Internet address	http://www.ieee-wcci2014.org/

Keywords

adaptive algorithms
differential evolution

Access to Document

10.1109/CEC.2014.6900587

Minisci-Vasile-CEC-2014-Adaptive-inflationary-differential-evolution-Jul-2014Accepted author manuscript, 1.55 MB

Cite this

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title = "Adaptive inflationary differential evolution",

abstract = "In this paper, an adaptive version of Inflationary Differential Evolution is presented and tested on a set of real case problems taken from the CEC2011 competition on realworld applications. Inflationary Differential Evolution extends standard Differential Evolution with both local and global restart procedures. The proposed adaptive algorithm utilizes a probabilistic kernel based approach to automatically adapt the values of both the crossover and step parameters. In addition the paper presents a sensitivity analysis on the values of the parameters controlling the local restart mechanism and their impact on the solution of one of the hardest problems in the CEC2011 test set.",

keywords = "adaptive algorithms, differential evolution",

author = "Edmondo Minisci and Massimiliano Vasile",

note = ".; CEC 2014 : IEEE Conference on Evolutionary computation ; Conference date: 06-07-2014 Through 11-07-2014",

year = "2014",

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doi = "10.1109/CEC.2014.6900587",

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AU - Vasile, Massimiliano

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N2 - In this paper, an adaptive version of Inflationary Differential Evolution is presented and tested on a set of real case problems taken from the CEC2011 competition on realworld applications. Inflationary Differential Evolution extends standard Differential Evolution with both local and global restart procedures. The proposed adaptive algorithm utilizes a probabilistic kernel based approach to automatically adapt the values of both the crossover and step parameters. In addition the paper presents a sensitivity analysis on the values of the parameters controlling the local restart mechanism and their impact on the solution of one of the hardest problems in the CEC2011 test set.

AB - In this paper, an adaptive version of Inflationary Differential Evolution is presented and tested on a set of real case problems taken from the CEC2011 competition on realworld applications. Inflationary Differential Evolution extends standard Differential Evolution with both local and global restart procedures. The proposed adaptive algorithm utilizes a probabilistic kernel based approach to automatically adapt the values of both the crossover and step parameters. In addition the paper presents a sensitivity analysis on the values of the parameters controlling the local restart mechanism and their impact on the solution of one of the hardest problems in the CEC2011 test set.

KW - adaptive algorithms

KW - differential evolution

UR - http://www.ieee.org/conferences_events/conferences/conferencedetails/index.html?Conf_ID=32438

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DO - 10.1109/CEC.2014.6900587

M3 - Paper

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T2 - CEC 2014

Y2 - 6 July 2014 through 11 July 2014

ER -

Adaptive inflationary differential evolution

Abstract

Conference

Keywords

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ARCHIE-WeSt (UOSHPC)

Adaptive multi-population inflationary differential evolution

Aerodynamic design optimization of wind turbine airfoils under aleatory and epistemic uncertainty

Cite this

Adaptive inflationary differential evolution

Abstract

Conference

Keywords

Access to Document

Other files and links

Fingerprint

Equipment

ARCHIE-WeSt (UOSHPC)

Research output

Adaptive multi-population inflationary differential evolution

Aerodynamic design optimization of wind turbine airfoils under aleatory and epistemic uncertainty

Cite this