Abstract
This paper shows how tools and techniques of artificial intelligence can be successfully integrated into a computer system working in the vehicle routing domain. The aim of this system, called ALTO, is to facilitate the development of routing algorithms for transportation vehicles. In this paper, we describe the general algorithmic framework and the rich interface provided by the system to the expert algorithm designer. We also introduce a methodology for acquiring useful knowledge in the domain, based on examples of successful and unsuccessful problem-solving strategies. With such knowledge, ALTO would then be capable of actively supporting the algorithm designer by suggesting good candidate algorithms for solving new problems.
This is a preview of subscription content, log in via an institution to check access.
Preview
Unable to display preview. Download preview PDF.
References
L. Bodin, B. Golden, A. Assad and M. Ball (1983) Routing and scheduling of vehicles and crews: the state of the art. Computers and Operations Research 10, 000–000.
D. Rosenkrantz, R. Sterns and P. Lewis (1977) An analysis of several heuristics for the travelling salesman problem. SIAM J. Comp. 6, 563–581.
F. Cullen, J. Jarvis and D. Ratliff (1981) Set partitioning based heuristics for interactive routing. Networks 11, 125–143.
P. Krolak, W. Felts and G. Marble (1971) A man-machine approach toward solving the traveling salesman problem. Commun. ACM 14, 327–334.
P. Krolak, W. Felts and J. Nelson (1972) A man-machine approach toward solving the generalized truck dispatching problem. Transportation Science 6, 149–170.
S. Lin (1965) Computer solutions of the traveling salesman problem. Bell System Tech. J. 44, 2245–2269.
J. Y. Potvin, G. Lapalme and J. M. Rousseau (1989) ALTO: A computer system for the design of vehicle routing algorithms. Computers and Operations Research 16, 451–470.
G. Lapalme, J. Y. Potvin and J. M. Rousseau (1988) A general heuristic for node routing problems. In Advances in Optimization and Control (H. A. Eiselt and G. Pendertzoli, Eds), pp. 124–143. Springer-Verlag, Berlin.
W. Teitelman and L. Masinter (1981) The interslip programming environment. Computer April 1981, 25–32.
J. Y. Potvin and S. F. Smith (1989) Flexible systems for the design of heuristic algorithms in complex OR domains. In Impacts of Recent Computer Advances on Operations Research, Publications in Operations Research Series, Vol. 9, (S. I. Gass. Ed.), pp. 332–344. Elsevier Science Publishing Co., New York.
J. A. Ferland, J. M. Rousseau and L. Chapleau (1985) Clustering for routing in densely populated areas. Eur. J. Opl Res. 20, 48–57.
T. G. Dietterich and R. S. Michalski (1983) A comparative review of selected methods for learning from examples. In Machine Learning: An Artificial Intelligence Approach (R. S. Michalski J. G. Carbonell and T. M. Mitchell, Eds), pp. 41–81. Tioga Publishing Co., Palo Alto, California.
T. M. Mitchell, P. E. Utgoff and R. Banerji (1983) Learning by experimentation: acquiring and refining problemsolving heuristics. In Machine Learning: An Artificial Intelligence Approach (R. S. Michalski, J. G. Carboneli, and T. M. Mitchell, Eds), pp. 163–190. Tioga Publishing Co., Palo Alto, California.
J. R. Quinlan (1979) Discovering rules by induction from large collections of examples. In Expert Systems in the Micro-Electronic Age (D. Michie, Ed.), pp. 169–201. Edinburgh University Press.
M. Desrochers C. V. Jones, J. K. Lenstra, M. W. P. Savelsbergh and L. Stougie (1989) Towards a Model and Algorithm Management System for Vehicle Routing and Scheduling Problems. Technical Report G-89–27, GERAD, Ecole des Hautes Etudes Commerciales, Université de Montréal.
J. Cendrowska (1987) PRISM: An algorithm for inducing modular rules. lnt. J. Man-Machine Studies 27, 349–370.
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Copyright information
© 1992 Operational Research Society Ltd
About this chapter
Cite this chapter
Potvin, JY., Lapalme, G., Rousseau, JM. (1992). Integration of AI and OR Techniques for Computer-aided Algorithmic Design in the Vehicle Routing Domain. In: Doukidis, G.I., Paul, R.J. (eds) Artificial Intelligence in Operational Research. Palgrave, London. https://doi.org/10.1007/978-1-349-12362-9_20
Download citation
DOI: https://doi.org/10.1007/978-1-349-12362-9_20
Publisher Name: Palgrave, London
Print ISBN: 978-1-349-12364-3
Online ISBN: 978-1-349-12362-9
eBook Packages: EngineeringEngineering (R0)