Abstract
In this paper, we focus on the resolution of Crew Pairing Optimization problem that is very visible and economically significant. Its objective is to find the best schedule, i.e., a collection of crew rotations such that each airline flight is covered by exactly one rotation and the costs are reduced to the minimum. We try to solve it with Ant Colony Optimization algorithms and Hybridizations of Ant Colony Optimization with Constraint Programming techniques. We give an illustrative example about the difficulty of pure Ant Algorithms solving strongly constrained problems. Therefore, we explore the addition of Constraint Programming mechanisms in the construction phase of the ants, so they can complete their solutions. Computational results solving some test instances of Airline Flight Crew Scheduling taken from NorthWest Airlines database are presented showing the advantages of using this kind of hybridization.
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References
Alexandrov, D., Kochetov, Y.: Behavior of the ant colony algorithm for the set covering problem. In: Proc. of Symp. Operations Research, pp. 255–260. Springer, Heidelberg (2000)
Andersson, E., Housos, E., Kohl, N., Wedelin, D.: Crew pairing optimization. In: Yu, G. (ed.) Operations Research in the Airline Industry. Kluwer Academic Publishers, Dordrecht (1998)
Apt, K.R.: Principles of Constraint Programming. Cambridge University Press, Cambridge (2003)
Balas, E., Padberg, M.: Set partitioning: A survey. SIAM Review 18, 710–760 (1976)
Beasley, J.E.: Or-library:distributing test problem by electronic mail. Journal of Operational Research Society 41(11), 1069–1072 (1990)
Beasley, J.E., Chu, P.C.: A genetic algorithm for the set covering problem. European Journal of Operational Research 94(2), 392–404 (1996)
Bessiere, C.: Constraint propagation. Technical Report 06020, LIRMM (March 2006); In: Rossi, F., van Beek, P., Walsh, T. (eds.) Handbook of Constraint Programming, ch. 3. Elsevier, Amsterdam (2006)
Castro, C., Moossen, M., Riff, M.-C.: A cooperative framework based on local search and constraint programming for solving discrete global optimisation. In: Bazzan, A.L.C., Labidi, S. (eds.) SBIA 2004. LNCS (LNAI), vol. 3171, pp. 93–102. Springer, Heidelberg (2004)
Chu, P.C., Beasley, J.E.: Constraint handling in genetic algorithms: the set partitoning problem. Journal of Heuristics 4, 323–357 (1998)
Dechter, R., Frost, D.: Backjump-based backtracking for constraint satisfaction problems. Artificial Intelligence 136, 147–188 (2002)
Dorigo, M., Caro, G.D., Gambardella, L.M.: Ant algorithms for discrete optimization. Artificial Life 5, 137–172 (1999)
Dorigo, M., Gambardella, L.M.: Ant colony system: A cooperative learning approach to the traveling salesman problem. IEEE Transactions on Evolutionary Computation 1(1), 53–66 (1997)
Dorigo, M., Stutzle, T.: Ant Colony Optimization. MIT Press, USA (2004)
Feo, A., Mauricio, G., Resende, A.: A probabilistic heuristic for a computationally difficult set covering problem. OR Letters 8, 67–71 (1989)
Focacci, F., Laburthe, F., Lodi, A.: Local search and constraint programming. Handbook of metaheuristics. Kluwer, Dordrecht (2002)
Gagne, C., Gravel, M., Price, W.: A look-ahead addition to the ant colony optimization metaheuristic and its application to an industrial scheduling problem. In: J.S., et al. (eds.) Proceedings of the fourth Metaheuristics International Conference MIC 2001, July 2001, pp. 79–84 (2001)
Gandibleux, X., Delorme, X., T’Kindt, V.: An ant colony optimisation algorithm for the set packing problem. In: Dorigo, M., Birattari, M., Blum, C., Gambardella, L.M., Mondada, F., Stützle, T. (eds.) ANTS 2004. LNCS, vol. 3172, pp. 49–60. Springer, Heidelberg (2004)
Hadji, R., Rahoual, M., Talbi, E., Bachelet, V.: Ant colonies for the set covering problem. In: Dorigo, M., et al. (eds.) ANTS 2000, pp. 63–66 (2000)
Leguizamón, G., Michalewicz, Z.: A new version of ant system for subset problems. In: Congress on Evolutionary Computation, CEC 1999, Piscataway, NJ, USA, pp. 1459–1464. IEEE Press, Los Alamitos (1999)
Lessing, L., Dumitrescu, I., Stützle, T.: A comparison between ACO algorithms for the set covering problem. In: Dorigo, M., Birattari, M., Blum, C., Gambardella, L.M., Mondada, F., Stützle, T. (eds.) ANTS 2004. LNCS, vol. 3172, pp. 1–12. Springer, Heidelberg (2004)
Maniezzo, V., Milandri, M.: An ant-based framework for very strongly constrained problems. In: Dorigo, M., Di Caro, G.A., Sampels, M. (eds.) Ant Algorithms 2002. LNCS, vol. 2463, pp. 222–227. Springer, Heidelberg (2002)
Meyer, B., Ernst, A.: Integrating ACO and constraint propagation. In: Dorigo, M., Birattari, M., Blum, C., Gambardella, L.M., Mondada, F., Stützle, T. (eds.) ANTS 2004. LNCS, vol. 3172, pp. 166–177. Springer, Heidelberg (2004)
Michel, R., Middendorf, M.: An island model based ant system with lookahead for the shortest supersequence problem. In: Eiben, A.E., Bäck, T., Schoenauer, M., Schwefel, H.-P. (eds.) PPSN 1998. LNCS, vol. 1498, pp. 692–701. Springer, Heidelberg (1998)
Rardin, R.L.: Optimization in Operations Research. Prentice-Hall, Englewood Cliffs (1998)
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Crawford, B., Castro, C., Monfroy, E. (2006). A Constructive Hybrid Algorithm for Crew Pairing Optimization. In: Euzenat, J., Domingue, J. (eds) Artificial Intelligence: Methodology, Systems, and Applications. AIMSA 2006. Lecture Notes in Computer Science(), vol 4183. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11861461_7
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DOI: https://doi.org/10.1007/11861461_7
Publisher Name: Springer, Berlin, Heidelberg
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