Abstract
This paper describes and compares several heuristic approaches for the car sequencing problem. We first study greedy heuristics, and show that dynamic ones clearly outperform their static counterparts. We then describe local search and ant colony optimization (ACO) approaches, that both integrate greedy heuristics, and experimentally compare them on benchmark instances. ACO yields the best solution quality for smaller time limits, and it is comparable to local search for larger limits. Our best algorithms proved one instance being feasible, for which it was formerly unknown whether it is satisfiable or not.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
A. Davenport and E.P. K. Tsang. Solving constraint satisfaction sequencing problems by iterative repair. In Proceedings of the First International Conference on the Practical Applications of Constraint Technologies and Logic Programming, 345–357, 1999
A. Davenport, E. Tsang, K. Zhu and C. Wang. GENET: a connectionist architecture for solving constraint satisfaction problems by iterative improvement. In Proceedings of AAAI’94, 325–330, 1994
M. Dincbas, H. Simonis and P. van Hentenryck. Solving the car-sequencing problem in constraint logic programming. In Proceedings of ECAI-88, 290–295, 1988
M. Dorigo and G. Di Caro. The Ant Colony Optimization Meta-Heuristic. In D. Corne, M. Dorigo, and F. Glover (eds.), New Ideas in Optimization, 11–32, McGraw Hill, UK, 1999
I.P. Gent. Two Results on Car-sequencing Problems. Technical report APES. 1998
I.P. Gent and T. Walsh. CSPLib: a benchmark library for constraints. Technical report APES-09-1999, available from http://4c.ucc.ie/~tw/csplib, a shorter version appeared in CP99, 1999
J.H.M. Lee, H.F. Leung and H.W. Won. Performance of a Comprehensive and Efficient Constraint Library using Local Search. In Proceedings of 11th Australian Joint Conference on Artificial Intelligence, 191–202, LNAI 1502, Springer, 1998
M. Puchta and J. Gottlieb. Solving Car Sequencing Problems by Local Optimization. In Applications of Evolutionary Computing, 132–142, LNCS 2279, Springer, 2002
J.-C. Regin and J.-F. Puget. A Filtering Algorithm for Global Sequencing Constraints. In Principles and Practice of Constraint Programming, 32–46, LNCS 1330, Springer, 1997
B. Smith. Succeed-first or fail-first: A case study in variable and value ordering heuristics. In Third Conference on the Practical Applications of Constraint Technology, 321–330, 1996
C. Solnon. Solving Permutation Constraint Satisfaction Problems with Artificial Ants. In Proceedings of ECAI-2000, 118–122, IOS Press, 2000
T. Stützle and H.H. Hoos. MAX-MIN Ant System. Journal of Future Generation Computer Systems, Volume 16, 889–914, 2000
E. Tsang. Foundations of Constraint Satisfaction. Academic Press, 1993
T. Warwick and E. Tsang. Tackling car sequencing problems using a genetic algorithm. Evolutionary Computation, Volume 3, Number 3, 267–298, 1995
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2003 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Gottlieb, J., Puchta, M., Solnon, C. (2003). A Study of Greedy, Local Search, and Ant Colony Optimization Approaches for Car Sequencing Problems. In: Cagnoni, S., et al. Applications of Evolutionary Computing. EvoWorkshops 2003. Lecture Notes in Computer Science, vol 2611. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-36605-9_23
Download citation
DOI: https://doi.org/10.1007/3-540-36605-9_23
Published:
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-00976-4
Online ISBN: 978-3-540-36605-8
eBook Packages: Springer Book Archive