@inproceedings{bb9a50e6158b4c7b9ef6476167a4fa81,
title = "An improved ant colony algorithm to solve knapsack problem",
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.",
keywords = "Ant colony optimization algorithm, Evolutionary computing, Knapsack problem",
author = "Shuang Li and Shuliang Wang and Qiuming Zhang",
year = "2006",
doi = "10.1117/12.713269",
language = "English",
isbn = "0819465283",
series = "Proceedings of SPIE - The International Society for Optical Engineering",
booktitle = "Geoinformatics 2006",
note = "Geoinformatics 2006: Remotely Sensed Data and Information ; Conference date: 28-10-2006 Through 29-10-2006",
}