Time Aggregation for Network Design to Meet Time-Constrained Demand

Title
Time Aggregation for Network Design to Meet Time-Constrained Demand
Publication Date
2013
Author(s)
Boland, N
Ernst, A
Kalinowski, T
( author )
OrcID: https://orcid.org/0000-0002-8444-6848
Email: tkalinow@une.edu.au
UNE Id une-id:tkalinow
Rocha de Paula, M
Savelsbergh, M
Singh, G
Editor
Editor(s): J Piantadosi, R S Anderssen and J Boland
Type of document
Conference Publication
Language
en
Entity Type
Publication
Publisher
Modelling and Simulation Society of Australia and New Zealand (MSSANZ)
Place of publication
Canberra, Australia
UNE publication id
une:1959.11/26784
Abstract
We study a network design problem inspired by a strategic planning problem encountered in the Hunter Valley Coal Chain. Demand is given in the form of freight that is available from a specific date and has to be transported from multiple origins to a single destination before its deadline. It is possible to temporarily store freight at certain intermediate locations along the way from origins to destination. The objective is to determine minimum-cost capacity expansions required on the links and nodes of the network, if any, so as to be able to transport all freight within its given time windows. A natural mixed integer programming formulation with a daily granularity quickly becomes computationally intractable. We investigate the potential of time aggregation to overcome the computational challenges. By aggregating consecutive time periods, a smaller instance is obtained, which can be solved more easily and provides a lower bound on the optimal value. A carefully designed iterative disaggregation scheme identifies a time aggregation that yields an optimal solution to the original problem. An extensive computational study demonstrates the efficacy of the proposed approach.
Link
Citation
MODSIM 2013: 20th International Congress on Modelling and Simulation - Adapting to change: the multiple roles of modelling, p. 3281-3287
ISBN
9780987214331
Start page
3281
End page
3287

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