ORCID Profile
0000-0001-7777-4213
Current Organisations
Northumbria University
,
Shahrood University of Technology
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Publisher: Elsevier BV
Date: 2023
Publisher: Elsevier BV
Date: 12-2013
Publisher: Elsevier BV
Date: 05-2017
Publisher: Elsevier BV
Date: 2017
Publisher: Elsevier BV
Date: 11-2017
Publisher: Informa UK Limited
Date: 23-04-2020
Publisher: Elsevier BV
Date: 12-2020
Publisher: Springer Science and Business Media LLC
Date: 28-10-2016
Publisher: Elsevier BV
Date: 12-2018
Publisher: Elsevier BV
Date: 09-2015
Publisher: Elsevier BV
Date: 10-2018
Publisher: Wiley
Date: 07-08-2020
DOI: 10.1111/DECI.12481
Abstract: We address the dynamic design of supply chain networks in which the moments of demand distribution function are uncertain and facilities’ availability is stochastic because of possible disruptions. To incorporate the existing stochasticity in our dynamic problem, we develop a multi‐stage stochastic program to specify the optimal location, capacity, inventory, and allocation decisions. Further, a data‐driven rolling horizon approach is developed to use observations of the random parameters in the stochastic optimization problem. In contrast to traditional stochastic programming approaches that are valid only for a limited number of scenarios, the rolling horizon approach makes the determined decisions by the stochastic program implementable in practice and evaluates them. The stochastic program is presented as a quadratic conic optimization, and to generate an efficient scenario tree, a forward scenario tree construction technique is employed. An extensive numerical study is carried out to investigate the applicability of the presented model and rolling horizon procedure, the efficiency of risk‐measurement policies, and the performance of the scenario tree construction technique. Several key practical and managerial insights related to the dynamic supply chain network design under uncertainty are gained based on the computational results.
Publisher: Springer Science and Business Media LLC
Date: 10-02-2023
Publisher: Elsevier BV
Date: 11-2019
Location: United Kingdom of Great Britain and Northern Ireland
Location: Iran (Islamic Republic of)
Location: Iran (Islamic Republic of)
No related grants have been discovered for Mohammad Fattahi.