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28 October 2006 An improved ant colony algorithm to solve knapsack problem
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Proceedings Volume 6419, Geoinformatics 2006: Remotely Sensed Data and Information; 64191T (2006) https://doi.org/10.1117/12.713269
Event: Geoinformatics 2006: GNSS and Integrated Geospatial Applications, 2006, Wuhan, China
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.
© (2006) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Shuang Li, Shuliang Wang, and Qiuming Zhang "An improved ant colony algorithm to solve knapsack problem", Proc. SPIE 6419, Geoinformatics 2006: Remotely Sensed Data and Information, 64191T (28 October 2006); https://doi.org/10.1117/12.713269
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