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.

[1]  Z. Michalewicz,et al.  A new version of ant system for subset problems , 1999, Proceedings of the 1999 Congress on Evolutionary Computation-CEC99 (Cat. No. 99TH8406).

[2]  John E. Beasley,et al.  OR-Library: Distributing Test Problems by Electronic Mail , 1990 .

[3]  K. Al-Sultan,et al.  A Genetic Algorithm for the Set Covering Problem , 1996 .

[4]  Manuel López-Ibáñez,et al.  Ant colony optimization , 2010, GECCO '10.

[5]  Michael J. Brusco,et al.  A morphing procedure to supplement a simulated annealing heuristic for cost‐ andcoverage‐correlated set‐covering problems , 1999, Ann. Oper. Res..

[6]  Martin Middendorf,et al.  An Island Model Based Ant System with Lookahead for the Shortest Supersequence Problem , 1998, PPSN.

[7]  Luca Maria Gambardella,et al.  Ant Algorithms for Discrete Optimization , 1999, Artificial Life.

[8]  E. Balas,et al.  Set Partitioning: A survey , 1976 .

[9]  Vincent T'Kindt,et al.  An Ant Colony Optimisation Algorithm for the Set Packing Problem , 2004, ANTS Workshop.

[10]  Luca Maria Gambardella,et al.  Ant colony system: a cooperative learning approach to the traveling salesman problem , 1997, IEEE Trans. Evol. Comput..

[11]  John E. Beasley,et al.  Constraint Handling in Genetic Algorithms: The Set Partitioning Problem , 1998, J. Heuristics.

[12]  Marc Gravel,et al.  A look-ahead addition to the ant colony optimization metaheuristic and its application to an industrial scheduling problem , 2001 .

[13]  M. Resende,et al.  A probabilistic heuristic for a computationally difficult set covering problem , 1989 .

[14]  Vittorio Maniezzo,et al.  An Ant-Based Framework for Very Strongly Constrained Problems , 2002, Ant Algorithms.

[15]  Andreas T. Ernst,et al.  Integrating ACO and Constraint Propagation , 2004, ANTS Workshop.

[16]  Thomas Stützle,et al.  A Comparison Between ACO Algorithms for the Set Covering Problem , 2004, ANTS Workshop.

[17]  Yuri Kochetov,et al.  Behavior of the Ant Colony Algorithm for the Set Covering Problem , 2000 .