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Conference Papers Year : 2004

A Study into Ant Colony Optimisation, Evolutionary Computation and Constraint Programming on Binary Constraint Satisfaction Problems

Des fourmis pour le sac-à-dos multi-dimensionnel


We compare two heuristic approaches, evolutionary computation and ant colony optimisation, and a complete tree-search approach, constraint programming, for solving binary constraint satisfaction problems. We experimentally show that, if evolutionary computation is far from being able to compete with the two other approaches, ant colony optimisation nearly always succeeds in finding a solution, so that it can actually compete with constraint programming. The resampling ratio is used to provide insight into heuristic algorithms performances. Regarding efficiency, we show that if constraint programming is the fastest when instances have a low number of variables, ant colony optimisation becomes faster when increasing the number of variables.
Des fourmis pour le sac-à-dos multi-dimensionnel
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hal-01541525 , version 1 (27-03-2020)


  • HAL Id : hal-01541525 , version 1


Inès Alaya, Christine Solnon, Khaled Ghedira. Des fourmis pour le sac-à-dos multi-dimensionnel. 4èmes Journées Francophones de Recherche Opérationnelle (Francoro 2004), May 2004, Lyon, France. pp.159-160. ⟨hal-01541525⟩
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