AbstractSuccessful heuristic algorithms for solving combinatorial optimization problems have mimicked processes observed in nature. Two highly successful families of algorithms that do this are simulated annealing and genetic algorithms. Here, a third family of algorithms, ant colony optimization is explored and implemented in C#. The test bed for evaluating the quality of solutions is based on several Traveling Salesperson Problems (TSP) of varying size using real-world data (Euclidian problems) with known solutions.
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About the author
Richard Wiener, "Ant Colony System Optimization", in Journal of Object Technology, vol. 8 no. 6, September-October 2009, pp. 39-58 http://www.jot.fm/issues/issue_2009_09/column4/ |
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