Abstract
In this paper, we apply the ant colony optimization metaheuristic to the Single Round Robin Maximum Value Problem, a problem from sports scheduling. This problem contains both feasibility constraints and an optimization goal. We approach this problem using a combination of the metaheuristic with backtracking search. We show how using constraint satisfaction techniques can improve the hybrid’s performance. We also show that our approach performs comparably to integer programming and better than tabu search when applied to the Single Round Robin Maximum Value Problem.
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Uthus, D.C., Riddle, P.J., Guesgen, H.W. (2008). Ant Colony Optimization and the Single Round Robin Maximum Value Problem. In: Dorigo, M., Birattari, M., Blum, C., Clerc, M., Stützle, T., Winfield, A.F.T. (eds) Ant Colony Optimization and Swarm Intelligence. ANTS 2008. Lecture Notes in Computer Science, vol 5217. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-87527-7_23
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DOI: https://doi.org/10.1007/978-3-540-87527-7_23
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