Citation
Rail Container Service Planning: A Constraint-Based Approach. In Selected papers from the 1st Multidisciplinary International Conference on Scheduling: Theory and Applications (MISTA), pages 343-368, Springer, 2005.
Selected
Abstract
This paper considers a container rail service planning problem, in which customer demands are known in advance. The existing rail freight optimisation models are complex and not demand responsive. This paper focuses on constructing profitable schedules, in which service supply matches customer demands and optimises on booking preferences whilst satisfying regulatory constraints. A constraint satisfaction approach is used, in which optimisation criteria and operational requirements are formulated as soft and hard constraints respectively. We present a constraint-based search algorithm capable of handling problems of realistic size. It employs a randomised strategy for the selection of constraints and variables to explore, and uses a predictive choice model to guide and intensify the search within more promising regions of the space. Experimental results, based on real data from the Royal State Railway of Thailand, have shown good computational performance of the approach and suggest significant benefits can be achieved for both the rail company and its customers.
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Bibtex
@INBOOK{2005-343-368-SI, chapter = {Selected papers from the 1st Multidisciplinary International Conference on Scheduling: Theory and Applications (MISTA)},
pages = {343--368},
title = {Rail Container Service Planning: A Constraint-Based Approach},
publisher = {Springer},
year = {2005},
editor = {G. Kendall and E. Burke and S. Petrovic and M. Gendreau},
author = {N. Indra-Payoong and R. S K Kwan and L. Proll},
note = {Selected},
abstract = {This paper considers a container rail service planning problem, in which customer demands are known in advance. The existing rail freight optimisation models are complex and not demand responsive. This paper focuses on constructing profitable schedules, in which service supply matches customer demands and optimises on booking preferences whilst satisfying regulatory constraints. A constraint satisfaction approach is used, in which optimisation criteria and operational requirements are formulated as soft and hard constraints respectively. We present a constraint-based search algorithm capable of handling problems of realistic size. It employs a randomised strategy for the selection of constraints and variables to explore, and uses a predictive choice model to guide and intensify the search within more promising regions of the space. Experimental results, based on real data from the Royal State Railway of Thailand, have shown good computational performance of the approach and suggest significant benefits can be achieved for both the rail company and its customers.},
doi = {10.1007/0-387-27744-7_17},
owner = {gxk},
timestamp = {2012.05.29} }