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by Management Science, Bernd Bullnheimer, Bernd Bullnheimer, Richard F. Hartl, Richard F. Hartl, Christine Strau, Christine Strau
http://www.bwl.univie.ac.at/bwl/prod/papers/pom-wp-3-97.ps
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Abstract:
The ant system is a new meta-heuristic for hard combinatorial optimization problems. It is a population-based approach that uses exploitation of positive feedback as well as greedy search. It was first proposed for tackling the well known Traveling Salesman Problem (TSP), but has been also successfully applied to problems such as quadratic assignment, job-shop scheduling, vehicle routing and graph colouring. In this paper we introduce a new rank based version of the ant system and present results of a computational study, where we compare the ant system with simulated annealing and a genetic algorithm on several TSP instances. It turns out that our rank based ant system can compete with the other methods in terms of average behavior, and shows even better worst case behavior. 1
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