Imperial College London
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DrMichel-AlexandreCardin

Faculty of Engineering, Dyson School of Design Engineering

Senior Lecturer in Computational Aided Engineering
 
 
 
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Contact

 

+44 (0)20 7594 1893m.cardin Website CV

 
 
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Location

 

Royal College of Science Observatory Building, Room 1M03Dyson BuildingSouth Kensington Campus

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Summary

 

Publications

Citation

BibTex format

@article{Zhao:2018:10.1080/24725854.2018.1426135,
author = {Zhao, S and Haskell, WB and Cardin, M-A},
doi = {10.1080/24725854.2018.1426135},
journal = {IISE Transactions},
pages = {553--569},
title = {Decision rule-based method for flexible multi-facility capacity expansion problem},
url = {http://dx.doi.org/10.1080/24725854.2018.1426135},
volume = {50},
year = {2018}
}
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RIS format (EndNote, RefMan)

TY  - JOUR
AB  - Strategic capacity planning for multiple-facility systems with flexible designs is an important topic in the area of capacity expansion problems with random demands. The difficulties of this problem lie in the multidimensional nature of its random variables and action space. For a single-facility problem, the decision rule method has been shown to be efficient in deriving desirable solutions, but for a Multiple-facility Capacity Expansion Problem (MCEP), it has not been well studied. This article designs a novel decision rule–based method for the solution of an MCEP with multiple options, discrete capacity, and a concave capacity expansion cost. An if–then decision rule is designed and the original multi-stage problem is thus transformed into a master problem and a multi-period sub-problem. As the sub-problem contains non-binding constraints, we combine a stochastic approximation algorithm with a branch-and-cut technique so that the sub-problem can be further decomposed across scenarios and be solved efficiently. The proposed decision rule–based method is also extended to solving the MCEP with fixed costs. Numerical studies in this article illustrate that the proposed method affords not only improved performance relative to an inflexible design taken as benchmark but also time savings relative to approximate dynamic programming analysis.
AU  - Zhao,S
AU  - Haskell,WB
AU  - Cardin,M-A
DO  - 10.1080/24725854.2018.1426135
EP  - 569
PY  - 2018///
SN  - 2472-5854
SP  - 553
TI  - Decision rule-based method for flexible multi-facility capacity expansion problem
T2  - IISE Transactions
UR  - http://dx.doi.org/10.1080/24725854.2018.1426135
UR  - http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000432174900001&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=1ba7043ffcc86c417c072aa74d649202
UR  - http://hdl.handle.net/10044/1/67109
VL  - 50
ER  -
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