Imperial College London
Alternate

Panagiotis Angeloudis

Faculty of Engineering, Department of Civil and Environmental Engineering

Reader in Transport Systems and Logistics
 
 
 
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Contact

 

+44 (0)20 7594 5986p.angeloudis Website

 
 
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Location

 

337Skempton BuildingSouth Kensington Campus

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Summary

 

Publications

Citation

BibTex format

@inproceedings{Hsu:2020:10.1016/j.trpro.2020.03.187,
author = {Hsu, PY and Aurisicchio, M and Angeloudis, P},
doi = {10.1016/j.trpro.2020.03.187},
pages = {245--252},
title = {Optimal logistics planning for modular construction using multi-stage stochastic programming},
url = {http://dx.doi.org/10.1016/j.trpro.2020.03.187},
year = {2020}
}
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RIS format (EndNote, RefMan)

TY  - CPAPER
AB  - The modular construction method has been adopted extensively by the construction sector for pursuing higher building quality and better project efficiency. However, the employment of this new construction method has not only altered the definition of construction supply chains, but also poses new challenges to the logistics system which has conventionally focused on raw material transportation. This challenge is exacerbated in the transport and inventory aspects when the project is executed in urban settings, owing to the frequent traffic congestion, crowded environment, as well as the bulkiness and delicacy of finished modules. This study develops a multi-stage stochastic programming model for identifying the optimal supply chain configuration for the modular construction method. Site demand is considered to be stochastic, forcing project managers to make several operational decisions at multiple time points during project execution. The developed model can provide the best production, transportation and inventory plans, as well as the most favourable initial inventory preparation schemes. Furthermore, we have proven that the implementation of multi-stage stochastic programming model can yield more economical and risk-averse solutions than the two-stage stochastic programming approach.
AU  - Hsu,PY
AU  - Aurisicchio,M
AU  - Angeloudis,P
DO  - 10.1016/j.trpro.2020.03.187
EP  - 252
PY  - 2020///
SN  - 2352-1457
SP  - 245
TI  - Optimal logistics planning for modular construction using multi-stage stochastic programming
UR  - http://dx.doi.org/10.1016/j.trpro.2020.03.187
ER  -
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