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Proceedings Paper

An improved ant colony algorithm to solve knapsack problem
Author(s): Shuang Li; Shuliang Wang; Qiuming Zhang
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Paper Abstract

Ant colony optimization algorithm is a novel simulated evolutionary algorithm, which provides a new method for complicated combinatorial optimization problems. In this paper the algorithm is used for solving the knapsack problem. It is improved in selection strategy and information modification, so that it can not easily run into the local optimum and can converge at the global optimum. The experiments show the robustness and the potential power of this kind of meta-heuristic algorithm.

Paper Details

Date Published: 28 October 2006
PDF: 7 pages
Proc. SPIE 6419, Geoinformatics 2006: Remotely Sensed Data and Information, 64191T (28 October 2006); doi: 10.1117/12.713269
Show Author Affiliations
Shuang Li, China Univ. of Geosciences (China)
Wuhan Univ. (China)
Shuliang Wang, Wuhan Univ. (China)
Qiuming Zhang, China Univ. of Geosciences (China)

Published in SPIE Proceedings Vol. 6419:
Geoinformatics 2006: Remotely Sensed Data and Information
Liangpei Zhang; Xiaoling Chen, Editor(s)

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