An improved ant colony algorithm to solve knapsack problem

Shuang Li; Shuliang Wang; Qiuming Zhang

doi:10.1117/12.713269

28 October 2006 An improved ant colony algorithm to solve knapsack problem

Shuang Li, Shuliang Wang, Qiuming Zhang

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.

Citation Download Citation

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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