Solving Constraint Satisfaction Problems by ACO with Cunning Ants

To solve large-scale constraint satisfaction problems, CSPs, ant colony optimization, ACO, based meta-heuristics has been used. However, the naive ACO based method is sometimes inefficient because the method may require much search time due to ant's reconstructing candidate solutions. In this paper, we describe an ant colony optimization based meta-heuristics with cunning ants in which artificial ants construct a candidate solution by partially using building blocks, or useful partial solutions, of the candidate solution constructed at the previous search generation in order to solve CSP instances. We also propose some methods for using building blocks and conduct some experimental simulations, demonstrating that how effective our method can be by variation of using the building blocks.

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