DocumentCode
2694459
Title
Solving multidimensional knapsack problems by an immune-inspired algorithm
Author
Guo, Shuiping ; Licheng Jiao ; Ma, Weping ; Shuiping Gou
Author_Institution
Xidian Univ., Xi´´an
fYear
2007
fDate
25-28 Sept. 2007
Firstpage
3385
Lastpage
3391
Abstract
This paper introduces a computational model simulating the dynamic process of human immune response to solve multidimensional knapsack problems. The new model is a quaternion (G, I, R, At), where G denotes exterior stimulus or antigen,denotes the set of valid antibodies, R denotes the set of reaction rules describing the interactions between antibodies, and Al denotes the dynamic algorithm describing how the reaction rules are applied to antibody population. The set of antibody-adjusting rules, the set of clonal selection rules, and a dynamic algorithm, named MKP-PAISA, are designed for solving multidimensional knapsack problems. The efficiency of the proposed algorithm was validated by testing on 57 benchmark problems and comparing with three genetic algorithms. The results indicated that the proposed algorithm was suitable for solving multidimensional knapsack problems.
Keywords
genetic algorithms; knapsack problems; antibodies; antibody-adjusting rules; antigen; clonal selection rules; computational model; dynamic algorithm; exterior stimulus; genetic algorithms; human immune response; immune-inspired algorithm; multidimensional knapsack problems; reaction rules; Evolutionary computation; Multidimensional systems; Testing;
fLanguage
English
Publisher
ieee
Conference_Titel
Evolutionary Computation, 2007. CEC 2007. IEEE Congress on
Conference_Location
Singapore
Print_ISBN
978-1-4244-1339-3
Electronic_ISBN
978-1-4244-1340-9
Type
conf
DOI
10.1109/CEC.2007.4424909
Filename
4424909
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