A Decision Support System for Supporting Strategic Production Allocation in the Automotive Industry

Edoardo Fadda, Guido Perboli, Mariangela Rosano, Julien Etienne Mascolo and Davide Masera
Additional contact information
Edoardo Fadda: DISMA and ICT for City Logistics and Enterprises Center, Politecnico di Torino, 10129 Turin, Italy
Guido Perboli: DIGEP and ICT for City Logistics and Enterprises Center, Politecnico di Torino, 10129 Turin, Italy
Mariangela Rosano: DIGEP and ICT for City Logistics and Enterprises Center, Politecnico di Torino, 10129 Turin, Italy
Julien Etienne Mascolo: Centro Ricerche Fiat, 10043 Turin, Italy
Davide Masera: Centro Ricerche Fiat, 10043 Turin, Italy

Sustainability, 2022, vol. 14, issue 4, 1-21

Abstract: This paper deals with the optimization problem faced by the manufacturing engineering department of an international automotive company, concerning its supply chain design (i.e., decisions regarding which plants to open, how many components to produce, and the logistic flow from production to assembly plants). The intrinsic characteristics of the problem, such as stochasticity, the high number of products and components, and exogenous factors, make it complex to formulate and solve the mathematical models. Thus, new decision support systems integrating human choices and fast solution algorithms are needed. In this paper, we present an innovative and successful use case of such an approach, encompassing the decision-maker as an integral part of the optimization process. Moreover, the proposed approach allows the managers to conduct what-if analyses in real-time, taking robust decisions with respect to future scenarios, while shortening the time needed. As a byproduct, the proposed methodology requires neither the definition of a probability distribution nor the investigation of the user’s risk aversion.

Keywords: decision support system; stochastic optimization; production allocation; automotive; industrial strategies (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://www.mdpi.com/2071-1050/14/4/2408/pdf (application/pdf)
https://www.mdpi.com/2071-1050/14/4/2408/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jsusta:v:14:y:2022:i:4:p:2408-:d:753699

Access Statistics for this article

Sustainability is currently edited by Ms. Alexandra Wu

More articles in Sustainability from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().