An Improved Genetic Algorithm for 0-1 Knapsack Problems

Author

Shen, Wei ; Xu, Beibei ; Huang, Jiang-ping

Author_Institution

Fac. of Inf. & Electron., Zhejiang Sci-Tech Univ., Hangzhou, China

fYear

2011

fDate

21-24 Sept. 2011

Firstpage

32

Lastpage

35

Abstract

The 0-1 knapsack problems is a problem in combinatorial optimization, which is NP-complete to solve exactly. A genetic algorithm is a kind of heuristic that mimics the process of natural evolution. We derived an improved solution for 0-1 knapsack problem based on the dual population genetic algorithm, which can overcome the defect of precocious and local convergence in iterative processes. The performance evaluation shows that the solution is better than the traditional genetic algorithm.

Keywords

combinatorial mathematics; genetic algorithms; iterative methods; knapsack problems; 0-1 knapsack problems; NP-complete problem; combinatorial optimization; genetic algorithm; iterative processes; natural evolution; Collaboration; Convergence; Encoding; Genetic algorithms; Genetics; Heuristic algorithms; Optimization; 0-1 knapsack problems; dual-population genetic algorithm; greedy criterion; population collaboration; sub-group competition;

fLanguage

English

Publisher

ieee

Conference_Titel

Networking and Distributed Computing (ICNDC), 2011 Second International Conference on

Conference_Location

Beijing

Print_ISBN

978-1-4577-0407-9

Type

conf

DOI

10.1109/ICNDC.2011.14

Filename

6047101