Very Strongly Constrained Problems: An Ant Colony Optimization Approach

Maniezzo, V. and Roffilli, M. (2006) Very Strongly Constrained Problems: An Ant Colony Optimization Approach. [Preprint]
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Ant Colony Optimization (ACO) is a class of metaheuristic algorithms sharing the common approach of constructing a solution on the basis of information provided both by a standard constructive heuristic and by previously constructed solutions. This paper is composed of three parts. The first one frames ACO in current trends of research on metaheuristics for combinatorial optimization. The second outlines current research within the ACO community, reporting recent results obtained on different problems, while the third part focuses on a particular research line, named ANTS, providing some details on the algorithm and presenting results recently obtained on a prototypical strongly constrained problem: the set partitioning problem.

Document type
Maniezzo, V.
Roffilli, M.
Ant colony optimization, set partitioning problem, hardly constrained problem, combinatorial optimization, metaheuristics
Deposit date
15 Jan 2008
Last modified
16 May 2011 12:07

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