Evolutionary algorithm for zero-one constrained optimization problems based on objective penalty function

Zhiqing Meng; Min Jiang; Chuangyin Dang

doi:10.1109/CIS.2010.36

Evolutionary algorithm for zero-one constrained optimization problems based on objective penalty function

Zhiqing Meng
, Min Jiang
, Chuangyin Dang

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

6 Citations (Scopus)

Abstract

In many evolutionary algorithms, it is very important way to use penalty function as a fitness function in order to solve many integer optimization problems. In this paper, we first define a new objective penalty function and give its some properties for integer constrained optimization problems. Then, we present an algorithm with global convergence for integer constrained optimization problems in theory. Moreover, based on the objective penalty function, a simple novel evolutionary algorithm to solve the zero-one constrained optimization problems is developed. Finally, numerical results of several examples show that the proposed evolutionary algorithm has a good performance for some zero-one optimization problems. © 2010 IEEE.

Original language	English
Title of host publication	Proceedings - 2010 International Conference on Computational Intelligence and Security, CIS 2010
Pages	132-136
DOIs	https://doi.org/10.1109/CIS.2010.36
Publication status	Published - 2010
Event	2010 International Conference on Computational Intelligence and Security, CIS 2010 - Nanning, China Duration: 11 Dec 2010 → 14 Dec 2010

Conference

Conference	2010 International Conference on Computational Intelligence and Security, CIS 2010
Place	China
City	Nanning
Period	11/12/10 → 14/12/10

Research Keywords

Evolutionary algorithm
Fitness function
Objective penalty function
Zero-one optimization problems

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10.1109/CIS.2010.36

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@inproceedings{287bfb48661141e3a04635af573b88d4,

title = "Evolutionary algorithm for zero-one constrained optimization problems based on objective penalty function",

abstract = "In many evolutionary algorithms, it is very important way to use penalty function as a fitness function in order to solve many integer optimization problems. In this paper, we first define a new objective penalty function and give its some properties for integer constrained optimization problems. Then, we present an algorithm with global convergence for integer constrained optimization problems in theory. Moreover, based on the objective penalty function, a simple novel evolutionary algorithm to solve the zero-one constrained optimization problems is developed. Finally, numerical results of several examples show that the proposed evolutionary algorithm has a good performance for some zero-one optimization problems. {\textcopyright} 2010 IEEE.",

keywords = "Evolutionary algorithm, Fitness function, Objective penalty function, Zero-one optimization problems",

author = "Zhiqing Meng and Min Jiang and Chuangyin Dang",

year = "2010",

doi = "10.1109/CIS.2010.36",

language = "English",

isbn = "9780769542973",

pages = "132--136",

booktitle = "Proceedings - 2010 International Conference on Computational Intelligence and Security, CIS 2010",

note = "2010 International Conference on Computational Intelligence and Security, CIS 2010 ; Conference date: 11-12-2010 Through 14-12-2010",

}

Meng, Z, Jiang, M & Dang, C 2010, Evolutionary algorithm for zero-one constrained optimization problems based on objective penalty function. in Proceedings - 2010 International Conference on Computational Intelligence and Security, CIS 2010., 5696248, pp. 132-136, 2010 International Conference on Computational Intelligence and Security, CIS 2010, Nanning, China, 11/12/10. https://doi.org/10.1109/CIS.2010.36

Evolutionary algorithm for zero-one constrained optimization problems based on objective penalty function. / Meng, Zhiqing; Jiang, Min; Dang, Chuangyin.
Proceedings - 2010 International Conference on Computational Intelligence and Security, CIS 2010. 2010. p. 132-136 5696248.

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

TY - GEN

T1 - Evolutionary algorithm for zero-one constrained optimization problems based on objective penalty function

AU - Meng, Zhiqing

AU - Jiang, Min

AU - Dang, Chuangyin

PY - 2010

Y1 - 2010

N2 - In many evolutionary algorithms, it is very important way to use penalty function as a fitness function in order to solve many integer optimization problems. In this paper, we first define a new objective penalty function and give its some properties for integer constrained optimization problems. Then, we present an algorithm with global convergence for integer constrained optimization problems in theory. Moreover, based on the objective penalty function, a simple novel evolutionary algorithm to solve the zero-one constrained optimization problems is developed. Finally, numerical results of several examples show that the proposed evolutionary algorithm has a good performance for some zero-one optimization problems. © 2010 IEEE.

AB - In many evolutionary algorithms, it is very important way to use penalty function as a fitness function in order to solve many integer optimization problems. In this paper, we first define a new objective penalty function and give its some properties for integer constrained optimization problems. Then, we present an algorithm with global convergence for integer constrained optimization problems in theory. Moreover, based on the objective penalty function, a simple novel evolutionary algorithm to solve the zero-one constrained optimization problems is developed. Finally, numerical results of several examples show that the proposed evolutionary algorithm has a good performance for some zero-one optimization problems. © 2010 IEEE.

KW - Evolutionary algorithm

KW - Fitness function

KW - Objective penalty function

KW - Zero-one optimization problems

UR - https://www.scopus.com/pages/publications/79951659612

UR - https://www.scopus.com/record/pubmetrics.uri?eid=2-s2.0-79951659612&origin=recordpage

U2 - 10.1109/CIS.2010.36

DO - 10.1109/CIS.2010.36

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

SN - 9780769542973

SP - 132

EP - 136

BT - Proceedings - 2010 International Conference on Computational Intelligence and Security, CIS 2010

T2 - 2010 International Conference on Computational Intelligence and Security, CIS 2010

Y2 - 11 December 2010 through 14 December 2010

ER -

Evolutionary algorithm for zero-one constrained optimization problems based on objective penalty function

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