Artificial immune antibody adjusting clonal algorithm for the 0-1 knapsack problem

Hai Feng Du; Ruo Chen Liu; Li Cheng Jiao; Sun An Wang

Artificial immune antibody adjusting clonal algorithm for the 0-1 knapsack problem

Hai Feng Du
, Ruo Chen Liu
, Li Cheng Jiao
, Sun An Wang

School of Public Policy and Administration

Xidian University
Xi'an Jiaotong University

Research output: Contribution to journal › Article › peer-review

6 Scopus citations

Abstract

Based on the clonal selection theory, the antibody-adjusting-clone operator is analyzed. A new artificial immune system algorithm, Artificial Immune Antibody Adjusting Clonal Algorithm (AIAACA), is put forward. Based on Markov chain theorem, the general artificial immune system algorithm is proved to be convergent. Compared with the Evolutionary Algorithm (EA), AIAACA is shown to be an evolutionary strategy to solve the combinatorial optimization problem, like 0-1 knapsack problem.

Original language	English
Pages (from-to)	348-352
Number of pages	5
Journal	Kongzhi Lilun Yu Yingyong/Control Theory and Applications
Volume	22
Issue number	3
State	Published - Jun 2005

Keywords

0-1 knapsack problem
Clonal selection
Evolutionary algorithms
Markov chain

Cite this

@article{102b9f705bec487d8fdef58b7c7ddf85,

title = "Artificial immune antibody adjusting clonal algorithm for the 0-1 knapsack problem",

abstract = "Based on the clonal selection theory, the antibody-adjusting-clone operator is analyzed. A new artificial immune system algorithm, Artificial Immune Antibody Adjusting Clonal Algorithm (AIAACA), is put forward. Based on Markov chain theorem, the general artificial immune system algorithm is proved to be convergent. Compared with the Evolutionary Algorithm (EA), AIAACA is shown to be an evolutionary strategy to solve the combinatorial optimization problem, like 0-1 knapsack problem.",

keywords = "0-1 knapsack problem, Clonal selection, Evolutionary algorithms, Markov chain",

author = "Du, \{Hai Feng\} and Liu, \{Ruo Chen\} and Jiao, \{Li Cheng\} and Wang, \{Sun An\}",

year = "2005",

month = jun,

language = "英语",

volume = "22",

pages = "348--352",

journal = "Kongzhi Lilun Yu Yingyong/Control Theory and Applications",

issn = "1000-8152",

publisher = "South China University of Technology",

number = "3",

}

TY - JOUR

T1 - Artificial immune antibody adjusting clonal algorithm for the 0-1 knapsack problem

AU - Du, Hai Feng

AU - Liu, Ruo Chen

AU - Jiao, Li Cheng

AU - Wang, Sun An

PY - 2005/6

Y1 - 2005/6

N2 - Based on the clonal selection theory, the antibody-adjusting-clone operator is analyzed. A new artificial immune system algorithm, Artificial Immune Antibody Adjusting Clonal Algorithm (AIAACA), is put forward. Based on Markov chain theorem, the general artificial immune system algorithm is proved to be convergent. Compared with the Evolutionary Algorithm (EA), AIAACA is shown to be an evolutionary strategy to solve the combinatorial optimization problem, like 0-1 knapsack problem.

AB - Based on the clonal selection theory, the antibody-adjusting-clone operator is analyzed. A new artificial immune system algorithm, Artificial Immune Antibody Adjusting Clonal Algorithm (AIAACA), is put forward. Based on Markov chain theorem, the general artificial immune system algorithm is proved to be convergent. Compared with the Evolutionary Algorithm (EA), AIAACA is shown to be an evolutionary strategy to solve the combinatorial optimization problem, like 0-1 knapsack problem.

KW - 0-1 knapsack problem

KW - Clonal selection

KW - Evolutionary algorithms

KW - Markov chain

UR - https://www.scopus.com/pages/publications/22844441186

M3 - 文章

AN - SCOPUS:22844441186

SN - 1000-8152

VL - 22

SP - 348

EP - 352

JO - Kongzhi Lilun Yu Yingyong/Control Theory and Applications

JF - Kongzhi Lilun Yu Yingyong/Control Theory and Applications

IS - 3

ER -

Artificial immune antibody adjusting clonal algorithm for the 0-1 knapsack problem

Abstract

Keywords

Other files and links

Fingerprint

Cite this