Ant Colonies for the QAP

This paper presents HAS-QAP, an hybrid ant colony system coupled with a local search, applied to the quadratic assignment problem. HAS-QAP uses pheromone trail information to perform modifications on QAP solutions, differently from more traditional ant systems that use pheromone trail information to construct complete solutions. HAS-QAP is analysed and compared with some of the best heuristics available for the QAP: two taboo search versions, that is, robust and reactive taboo search, an hybrid genetic algorithm, and a simulated annealing. Experimental results show that HAS-QAP and the hybrid genetic algorithm are the best performing on real world, irregular and structured problems due to their ability in finding the structure of good solutions, while HAS-QAP performance is less competitive on random, regular and unstructured problems.