Citation
A Decomposition Approach for Shipment Pickup and Delivery with Time-Windows Under Uncertainty. In proceedings of the 5th Multidisciplinary International Conference on Scheduling : Theory and Applications (MISTA 2011), 9-11 August 2011, Phoenix, Arizona, USA, pages 352-365, 2011.
Paper
Abstract
We consider a special class of large-scale, network-based, resource allocation problems under uncertainty, namely that of multi-commodity flows with time-windows under uncertainty. In this class, we focus on problems involving shipment pickup and delivery with time windows, with the goal of gaining insights applicable to the broader problem class. Our work examines methods of proactive planning, that is, robust plan generation to protect against future uncertainty. By a priori modeling uncertainties in data corresponding to service times, resource availability, supplies and demands, we generate solutions that are more robust operationally, that is, more likely to be executed or easier to repair when disrupted. We propose a novel modeling and solution framework involving a decomposition scheme that separates problems into a routing master problem and scheduling sub-problems; and iterates to find the optimal solution. Uncertainty is captured in part by the master problem and in part by the sub-problem. Finally, we present computational experiments on a scaled-down version of a shipment carrier's network and on a larger airline's network.
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Bibtex
@INPROCEEDINGS{2011-352-365-P, author = {L. Marla and C. Barnhart},
title = {A Decomposition Approach for Shipment Pickup and Delivery with Time-Windows Under Uncertainty},
booktitle = {In proceedings of the 5th Multidisciplinary International Conference on Scheduling : Theory and Applications (MISTA 2011), 9-11 August 2011, Phoenix, Arizona, USA},
year = {2011},
editor = {J. Fowler and G. Kendall and B. McCollum},
pages = {352--365},
note = {Paper},
abstract = {We consider a special class of large-scale, network-based, resource allocation problems under uncertainty, namely that of multi-commodity flows with time-windows under uncertainty. In this class, we focus on problems involving shipment pickup and delivery with time windows, with the goal of gaining insights applicable to the broader problem class. Our work examines methods of proactive planning, that is, robust plan generation to protect against future uncertainty. By a priori modeling uncertainties in data corresponding to service times, resource availability, supplies and demands, we generate solutions that are more robust operationally, that is, more likely to be executed or easier to repair when disrupted. We propose a novel modeling and solution framework involving a decomposition scheme that separates problems into a routing master problem and scheduling sub-problems; and iterates to find the optimal solution. Uncertainty is captured in part by the master problem and in part by the sub-problem. Finally, we present computational experiments on a scaled-down version of a shipment carrier's network and on a larger airline's network.},
owner = {gxk},
timestamp = {2011.08.15},
webpdf = {2011-352-365-P.pdf} }