Article

Article title ABOUT SOME MODIFICATION OF ANT COLONY OPTIMIZATION
Authors V.M. Kurejchik, A.A. Kazharov
Section SECTION I. EVOLUTIONARY MODELING, GENETIC AND BIONIC ALGORITHMS
Month, Year 04, 2008 @en
Index UDC 007(075)
DOI
Abstract This paper is dedicated to the developing of modifications of ant colony optimization (ACO) for the solving of a classical NP-complete task – traveling salesman problem. Modeling of behavior of ants is the main idea of this algorithm. A computer program was created during this work. This program realizes the model of ants’ behavior with modifications. Results of the investigations allow to judge about optimum choice of parameters of ACO for traveling salesman problem. Experimental researches have proved efficiency of the modified ACO in comparison with standard ACO and genetic algorithms.

Download PDF

Keywords ant colony optimization, ACO, traveling salesman problem, TSP, NP task, VLSI, genetic algorithms.
References 1. Штовба С.Д. Муравьиные алгоритмы. – 2003.
2. Bonavear F., Dorigo M. Swarm Intelligence: from Natural to Artificial Systems. Oxford university Press. 1999.
3. Corne D., Dorigo M., Glover F. New Ideas in Optimization. McGrav-Hill. 1999.
4. http://iridia.ulb.ac.be/dorigo/ACO/ACO.html.
5. МакКоннелл Дж. Основы современных алгоритмов. – М.: Техносфера, 2004.
6. Гладков Л.А., Курейчик В.М., Курейчик В.В. Генетические алгоритмы. – Ростов-на-Дону: ООО «Ростиздат», 2004.
7. Kureichick V. M., Miagkikh V. V., Topchy A. P. Genetic Algorithm for Solution of the Traveling Salesman Problem with New Features against Premature Convergence.

Comments are closed.