Parameter control by the entire search history: Case study of history-driven evolutionary algorithm

Shing Wa Leung; Shiu Yin Yuen; Chi Kin Chow

doi:10.1109/CEC.2010.5585945

Parameter control by the entire search history: Case study of history-driven evolutionary algorithm

Shing Wa Leung, Shiu Yin Yuen, Chi Kin Chow

Department of Electrical Engineering

Research output: Chapters, Conference Papers, Creative and Literary Works › RGC 32 - Refereed conference paper (with host publication) › peer-review

7 Citations (Scopus)

Abstract

History-driven Evolutionary Algorithm (HdEA) is an EA that uses the entire search history to improve searching performance. By building the approximated fitness landscape and estimating the gradient using the entire history, HdEA performs a parameter-less adaptive mutation. In order to decrease the number of parameters that makes the HdEA more robust, this paper proposes a novel adaptive parameter control system. This system is as an add-on component to HdEA, which uses the whole search history in HdEA to control the parameters in an automatic manner. The performance of the proposed system is examined on 34 benchmark functions. The results shows that the parameter control system gives similar or better performance in 24 functions and has the benefit that two parameters of the HdEA are eliminated; they are set and varied automatically by the system. © 2010 IEEE.

Original language	English
Title of host publication	2010 IEEE World Congress on Computational Intelligence, WCCI 2010 - 2010 IEEE Congress on Evolutionary Computation, CEC 2010
DOIs	https://doi.org/10.1109/CEC.2010.5585945
Publication status	Published - 2010
Event	2010 6th IEEE World Congress on Computational Intelligence, WCCI 2010 - 2010 IEEE Congress on Evolutionary Computation, CEC 2010 - Barcelona, Spain Duration: 18 Jul 2010 → 23 Jul 2010

Conference

Conference	2010 6th IEEE World Congress on Computational Intelligence, WCCI 2010 - 2010 IEEE Congress on Evolutionary Computation, CEC 2010
Place	Spain
City	Barcelona
Period	18/07/10 → 23/07/10

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@inproceedings{4e373ac3da43404f93e7b375eca929c5,

title = "Parameter control by the entire search history: Case study of history-driven evolutionary algorithm",

abstract = "History-driven Evolutionary Algorithm (HdEA) is an EA that uses the entire search history to improve searching performance. By building the approximated fitness landscape and estimating the gradient using the entire history, HdEA performs a parameter-less adaptive mutation. In order to decrease the number of parameters that makes the HdEA more robust, this paper proposes a novel adaptive parameter control system. This system is as an add-on component to HdEA, which uses the whole search history in HdEA to control the parameters in an automatic manner. The performance of the proposed system is examined on 34 benchmark functions. The results shows that the parameter control system gives similar or better performance in 24 functions and has the benefit that two parameters of the HdEA are eliminated; they are set and varied automatically by the system. {\textcopyright} 2010 IEEE.",

author = "Leung, {Shing Wa} and Yuen, {Shiu Yin} and Chow, {Chi Kin}",

year = "2010",

doi = "10.1109/CEC.2010.5585945",

language = "English",

isbn = "9781424469109",

booktitle = "2010 IEEE World Congress on Computational Intelligence, WCCI 2010 - 2010 IEEE Congress on Evolutionary Computation, CEC 2010",

note = "2010 6th IEEE World Congress on Computational Intelligence, WCCI 2010 - 2010 IEEE Congress on Evolutionary Computation, CEC 2010 ; Conference date: 18-07-2010 Through 23-07-2010",

}

Leung, SW, Yuen, SY & Chow, CK 2010, Parameter control by the entire search history: Case study of history-driven evolutionary algorithm. in 2010 IEEE World Congress on Computational Intelligence, WCCI 2010 - 2010 IEEE Congress on Evolutionary Computation, CEC 2010., 5585945, 2010 6th IEEE World Congress on Computational Intelligence, WCCI 2010 - 2010 IEEE Congress on Evolutionary Computation, CEC 2010, Barcelona, Spain, 18/07/10. https://doi.org/10.1109/CEC.2010.5585945

Parameter control by the entire search history: Case study of history-driven evolutionary algorithm. / Leung, Shing Wa; Yuen, Shiu Yin; Chow, Chi Kin.
2010 IEEE World Congress on Computational Intelligence, WCCI 2010 - 2010 IEEE Congress on Evolutionary Computation, CEC 2010. 2010. 5585945.

Research output: Chapters, Conference Papers, Creative and Literary Works › RGC 32 - Refereed conference paper (with host publication) › peer-review

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T2 - 2010 6th IEEE World Congress on Computational Intelligence, WCCI 2010 - 2010 IEEE Congress on Evolutionary Computation, CEC 2010

AU - Leung, Shing Wa

AU - Yuen, Shiu Yin

AU - Chow, Chi Kin

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Y1 - 2010

N2 - History-driven Evolutionary Algorithm (HdEA) is an EA that uses the entire search history to improve searching performance. By building the approximated fitness landscape and estimating the gradient using the entire history, HdEA performs a parameter-less adaptive mutation. In order to decrease the number of parameters that makes the HdEA more robust, this paper proposes a novel adaptive parameter control system. This system is as an add-on component to HdEA, which uses the whole search history in HdEA to control the parameters in an automatic manner. The performance of the proposed system is examined on 34 benchmark functions. The results shows that the parameter control system gives similar or better performance in 24 functions and has the benefit that two parameters of the HdEA are eliminated; they are set and varied automatically by the system. © 2010 IEEE.

AB - History-driven Evolutionary Algorithm (HdEA) is an EA that uses the entire search history to improve searching performance. By building the approximated fitness landscape and estimating the gradient using the entire history, HdEA performs a parameter-less adaptive mutation. In order to decrease the number of parameters that makes the HdEA more robust, this paper proposes a novel adaptive parameter control system. This system is as an add-on component to HdEA, which uses the whole search history in HdEA to control the parameters in an automatic manner. The performance of the proposed system is examined on 34 benchmark functions. The results shows that the parameter control system gives similar or better performance in 24 functions and has the benefit that two parameters of the HdEA are eliminated; they are set and varied automatically by the system. © 2010 IEEE.

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DO - 10.1109/CEC.2010.5585945

M3 - RGC 32 - Refereed conference paper (with host publication)

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BT - 2010 IEEE World Congress on Computational Intelligence, WCCI 2010 - 2010 IEEE Congress on Evolutionary Computation, CEC 2010

Y2 - 18 July 2010 through 23 July 2010

ER -

Parameter control by the entire search history: Case study of history-driven evolutionary algorithm

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