Abstract
PISCES is an integrated system for intermodal transport that is focused on the real time exchange of operation critical information via the WWW, and on the transport scheduling. The particular aspect of PISCES dealt with in this paper is the use of that information to provide high-quality scheduling of container traffic using genetic algorithms and constraint satisfaction technology.
Keywords
- Constraint Satisfaction Problem
- Vehicle Route Problem
- Empty Container
- Vehicle Route Problem With Time Window
- Container Transport
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsPreview
Unable to display preview. Download preview PDF.
References
Gilles Pesant, Michel Gendreau, Jean-Yves Potvin and Jean-Marc Rousseau, “An Exact Constraint Logic Programming Algorithm for the Traveling Salesman Problem with Time Windows”Transportation Science 32, 12 - 29 (1998).
M. Savelsbergh, M. Sol: “The General Pickup and Delivery Problem”. Transportation Science 29, 1995.
F. Arshad, A. El Rhalibi, G. Kelleher, “Information Management within Intermodal Transport Chain Scheduling” EMMSEC’99, June 21–23 1999, Stockholm - Sweden.
A.A. Assad, B.L. Golden. “Vehicle Routing with Time-Window Constraints: Algorithmic Solutions”. American Series in Mathematical and Management Sciences. Vol 15, American Science Press, Inc., Colombus, Ohio. 1986.
J. Lenstra, A. Rinnooy Kan, “Complexity of Vehicle Routing and Scheduling Problems”. Network, 11. 1981.
Smith, S. F., Cheng-Chung, C: “Applying Constraint Satisfaction Techniques to Job-Shop Scheduling”. The Robotics Institute, Carnegie Mellon University, Pittsburgh, PA 15213, CMU-RI-TR9–95-03. 1995.
G. Kelleher and J. E. Spragg: “A Discipline for Reactive Rescheduling”. 3rd International Conference on Artificial Intelligence Planning Systems (AIPS-96), AAAI Press, Edinburgh, Scotland, 1996.
D. E. Goldberg: “Genetic Algorithms in Search, Optimization, and Machine Learning”. Addison—Wesley, Reading, Massachusetts, 1989.
Le Pape, C. (1994). “Constrained-Based Programming for Scheduling: An Historical Perspective”. Operations Research Society Seminar on Constraint Handling Techniques, London, UK.
Steven Minton, Mark D.Johnston, Andrew B. Phillips, and Philip Laird, “Solving Large-scale constraint satisfaction and scheduling problems using a heuristic repair method”, AAAI-90 (Boston, MA ), 1990, pp. 1724.
M.M. Solomon, “VRPTW Benchmark Problems”,http://www.cba.neu.edu/-msolomon/problems.htm
Rochat, Y. and Taillard, E.D., Probabilistic diversification and intensification in local search for vehicle routing. Journal of Heuristics, Vol. 1, No. 1, 1995, pp. 147 - 167.
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2000 Springer-Verlag London
About this paper
Cite this paper
Arshad, F., El-Rhalibi, A., Kelleher, G. (2000). Constraints and Genetic Algorithm to Solve Transport Scheduling. In: Ellis, R., Moulton, M., Coenen, F. (eds) Applications and Innovations in Intelligent Systems VII. Springer, London. https://doi.org/10.1007/978-1-4471-0465-0_16
Download citation
DOI: https://doi.org/10.1007/978-1-4471-0465-0_16
Publisher Name: Springer, London
Print ISBN: 978-1-85233-230-3
Online ISBN: 978-1-4471-0465-0
eBook Packages: Springer Book Archive