Ant Colony System Optimization

By Richard Wiener



PDF Icon
PDF Version


Successful 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.


Note: Due to the typographical sophistication of this article, no HTML version is available. Please use the PDF version.


About the author


Richard Wiener is Chair of Computer Science at the University of Colorado at Colorado Springs. He is also the Editor-in-Chief of JOT and former Editor-in-Chief of the Journal of Object Oriented Programming. In addition to University work, Dr. Wiener has authored or co-authored 22 books and works actively as a consultant and software contractor whenever the possibility arises. His latest book, published by Thomson, Course Technology in April 2006, is entitled Modern Software Development Using C#/.NET.

Richard Wiener, "Ant Colony System Optimization", in Journal of Object Technology, vol. 8 no. 6, September-October 2009, pp. 39-58

Previous column

Next column