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A Novel ACO with Average Entropy

Abstract PP. 370-374
DOI: 10.4236/jsea.2009.25049    3,658 Downloads   6,718 Views   Citations
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ABSTRACT

In order to solve the premature convergence problem of the basic Ant Colony Optimization algorithm, a promising modification with changing index was proposed. The main idea of the modification is to measure the uncertainty of the path selection and evolution by using the average information entropy self-adaptively. Simulation study and perform-ance comparison on Traveling Salesman Problem show that the improved algorithm can converge at the global opti-mum with a high probability. The work provides a new approach for solving the combinatorial optimization problems, especially the NP-hard combinatorial optimization problems.

Conflicts of Interest

The authors declare no conflicts of interest.

Cite this paper

Y. LI, "A Novel ACO with Average Entropy," Journal of Software Engineering and Applications, Vol. 2 No. 5, 2009, pp. 370-374. doi: 10.4236/jsea.2009.25049.

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