Integrating Lookahead and Post Processing Procedures with ACO for Solving Set Partitioning and Covering Problems
Set Covering Problems and Set Partitioning Problems can model several real life situations. In this paper, we solve some benchmarks of them with Ant Colony Optimization algorithms and some hybridizations of Ant Colony Optimization with Constraint Programming techniques. A lookahead mechanism allows the incorporation of information on the anticipated decisions that are beyond the immediate choice horizon. The ants solutions may contain redundant components which can be eliminated by a fine tuning after the solution, then we explore Post Processing procedures too, which consist in the identification and replacement of the columns of the ACO solution in each iteration by more effective columns. Computational results are presented showing the advantages to use additional mechanisms to Ant Colony Optimization.
KeywordsConstraint Program Pheromone Trail Heuristic Information Post Processing Procedure Forward Check
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