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CPAIOR
2010
Springer

Strong Combination of Ant Colony Optimization with Constraint Programming Optimization

9 years 3 months ago
Strong Combination of Ant Colony Optimization with Constraint Programming Optimization
We introduce an approach which combines ACO (Ant Colony Optimization) and IBM ILOG CP Optimizer for solving COPs (Combinatorial Optimization Problems). The problem is modeled using the CP Optimizer modeling API. Then, it is solved in a generic way by a two-phase algorithm. The first phase aims at creating a hot start for the second: it samples the solution space and applies reinforcement learning techniques as implemented in ACO to create pheromone trails. During the second phase, CP Optimizer performs a complete tree search guided by the pheromone trails previously accumulated. The first experimental results on knapsack, quadratic assignment and maximum independent set problems show that this new algorithm enhances the performance of CP Optimizer alone.
Madjid Khichane, Patrick Albert, Christine Solnon
Added 19 Jul 2010
Updated 19 Jul 2010
Type Conference
Year 2010
Where CPAIOR
Authors Madjid Khichane, Patrick Albert, Christine Solnon
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