DocumentCode
627232
Title
An evolutionary algorithm with masked mutation for 0/1 knapsack problem
Author
Khan, Mozammel H. A.
Author_Institution
Dept. of Comput. Sci. & Eng., East West Univ., Dhaka, Bangladesh
fYear
2013
fDate
17-18 May 2013
Firstpage
1
Lastpage
6
Abstract
We propose a new evolutionary algorithm (EA) for single-objective 0/1 knapsack problem, which uses a single variation operator called masked mutation. The proposed EA outperforms the quantum-inspired evolutionary algorithm for 0/1 knapsack problem, which is shown to outperform Genetic Algorithms for 0/1 knapsack problem. The proposed EA generates profits that are equal to or nearly equal to that produced by the classical approximation algorithm for 0/1 knapsack problem.
Keywords
combinatorial mathematics; evolutionary computation; knapsack problems; EA; evolutionary algorithm; masked mutation; single variation operator; single-objective 0/1 knapsack problem; Approximation algorithms; Approximation methods; Evolutionary computation; Heuristic algorithms; Polynomials; Sociology; Statistics; 0/1 knapsack problem; combinatorial optimization; evolutionary algorithm; masked mutation;
fLanguage
English
Publisher
ieee
Conference_Titel
Informatics, Electronics & Vision (ICIEV), 2013 International Conference on
Conference_Location
Dhaka
Print_ISBN
978-1-4799-0397-9
Type
conf
DOI
10.1109/ICIEV.2013.6572583
Filename
6572583
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