IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v14y2022i4p2408-d753699.html
   My bibliography  Save this article

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

Author

Listed:
  • Edoardo Fadda

    (DISMA and ICT for City Logistics and Enterprises Center, Politecnico di Torino, 10129 Turin, Italy
    These authors contributed equally to this work.)

  • Guido Perboli

    (DIGEP and ICT for City Logistics and Enterprises Center, Politecnico di Torino, 10129 Turin, Italy
    Centre Interuniversitaire de Recherche sur les Reseaux D’entreprise, la Logistique et le Transport, Montreal, QC H3T 1J4, Canada
    These authors contributed equally to this work.)

  • Mariangela Rosano

    (DIGEP and ICT for City Logistics and Enterprises Center, Politecnico di Torino, 10129 Turin, Italy
    These authors contributed equally to this work.)

  • Julien Etienne Mascolo

    (Centro Ricerche Fiat, 10043 Turin, Italy)

  • Davide Masera

    (Centro Ricerche Fiat, 10043 Turin, Italy)

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.

Suggested Citation

  • Edoardo Fadda & Guido Perboli & Mariangela Rosano & Julien Etienne Mascolo & Davide Masera, 2022. "A Decision Support System for Supporting Strategic Production Allocation in the Automotive Industry," Sustainability, MDPI, vol. 14(4), pages 1-21, February.
    • Handle: RePEc:gam:jsusta:v:14:y:2022:i:4:p:2408-:d:753699
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/14/4/2408/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/14/4/2408/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Guido Perboli & Stefano Musso & Mariangela Rosano & Roberto Tadei & Moritz Godel, 2017. "Synchro-Modality and Slow Steaming: New Business Perspectives in Freight Transportation," Sustainability, MDPI, vol. 9(10), pages 1-24, October.
    2. Qin, Yan & Wang, Ruoxuan & Vakharia, Asoo J. & Chen, Yuwen & Seref, Michelle M.H., 2011. "The newsvendor problem: Review and directions for future research," European Journal of Operational Research, Elsevier, vol. 213(2), pages 361-374, September.
    3. Constantiou, Ioanna D & Kallinikos, Jannis, 2015. "New games, new rules: big data and the changing context of strategy," LSE Research Online Documents on Economics 63017, London School of Economics and Political Science, LSE Library.
    4. Luce Brotcorne & Guido Perboli & Mariangela Rosano & Qu Wei, 2019. "A Managerial Analysis of Urban Parcel Delivery: A Lean Business Approach," Sustainability, MDPI, vol. 11(12), pages 1-23, June.
    5. Powell, Warren B., 2019. "A unified framework for stochastic optimization," European Journal of Operational Research, Elsevier, vol. 275(3), pages 795-821.
    6. Edoardo Fadda & Luca Gobbato & Guido Perboli & Mariangela Rosano & Roberto Tadei, 2018. "Waste Collection in Urban Areas: A Case Study," Interfaces, INFORMS, vol. 48(4), pages 307-322, August.
    7. Chia-Nan Wang & Ngoc-Ai-Thy Nguyen & Thanh-Tuan Dang & Chen-Ming Lu, 2021. "A Compromised Decision-Making Approach to Third-Party Logistics Selection in Sustainable Supply Chain Using Fuzzy AHP and Fuzzy VIKOR Methods," Mathematics, MDPI, vol. 9(8), pages 1-27, April.
    8. M. A. H. Dempster & M. L. Fisher & L. Jansen & B. J. Lageweg & J. K. Lenstra & A. H. G. Rinnooy Kan, 1983. "Analysis of Heuristics for Stochastic Programming: Results for Hierarchical Scheduling Problems," Mathematics of Operations Research, INFORMS, vol. 8(4), pages 525-537, November.
    9. Ngoc Bao Tu Nguyen & Gu-Hong Lin & Thanh-Tuan Dang, 2021. "A Two Phase Integrated Fuzzy Decision-Making Framework for Green Supplier Selection in the Coffee Bean Supply Chain," Mathematics, MDPI, vol. 9(16), pages 1-22, August.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Erfan Ghorbani & Mahdi Alinaghian & Gevork. B. Gharehpetian & Sajad Mohammadi & Guido Perboli, 2020. "A Survey on Environmentally Friendly Vehicle Routing Problem and a Proposal of Its Classification," Sustainability, MDPI, vol. 12(21), pages 1-71, October.
    2. Crainic, Teodor Gabriel & Perboli, Guido & Rei, Walter & Rosano, Mariangela & Lerma, Veronica, 2024. "Capacity planning with uncertainty on contract fulfillment," European Journal of Operational Research, Elsevier, vol. 314(1), pages 152-175.
    3. Perboli, Guido & Brotcorne, Luce & Bruni, Maria Elena & Rosano, Mariangela, 2021. "A new model for Last-Mile Delivery and Satellite Depots management: The impact of the on-demand economy," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 145(C).
    4. Riccardo Giusti & Chiara Iorfida & Yuanyuan Li & Daniele Manerba & Stefano Musso & Guido Perboli & Roberto Tadei & Shuai Yuan, 2019. "Sustainable and De-Stressed International Supply-Chains Through the SYNCHRO-NET Approach," Sustainability, MDPI, vol. 11(4), pages 1-26, February.
    5. Michela Apruzzese & Maria Elena Bruni & Stefano Musso & Guido Perboli, 2023. "5G and Companion Technologies as a Boost in New Business Models for Logistics and Supply Chain," Sustainability, MDPI, vol. 15(15), pages 1-17, August.
    6. Moon, Ilkyeong & Feng, Xuehao, 2017. "Supply chain coordination with a single supplier and multiple retailers considering customer arrival times and route selection," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 106(C), pages 78-97.
    7. Mofidi, Seyed Shahab & Pazour, Jennifer A. & Roy, Debjit, 2018. "Proactive vs. reactive order-fulfillment resource allocation for sea-based logistics," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 114(C), pages 66-84.
    8. Gangopadhyay, Partha & Jain, Siddharth & Bakry, Walid, 2022. "In search of a rational foundation for the massive IT boom in the Australian banking industry: Can the IT boom really drive relationship banking?," International Review of Financial Analysis, Elsevier, vol. 82(C).
    9. Benedikt Finnah, 2022. "Optimal bidding functions for renewable energies in sequential electricity markets," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 44(1), pages 1-27, March.
    10. Serrano, Breno & Minner, Stefan & Schiffer, Maximilian & Vidal, Thibaut, 2024. "Bilevel optimization for feature selection in the data-driven newsvendor problem," European Journal of Operational Research, Elsevier, vol. 315(2), pages 703-714.
    11. Preil, Deniz & Krapp, Michael, 2022. "Bandit-based inventory optimisation: Reinforcement learning in multi-echelon supply chains," International Journal of Production Economics, Elsevier, vol. 252(C).
    12. Mohd Syaiful Rizal Abd Hamid & Nor Ratna Masrom & Nur Athirah Binti Mazlan, 2022. "The Key Factors of the Industrial Revolution 4.0 in the Malaysian Smart Manufacturing Context," International Journal of Asian Business and Information Management (IJABIM), IGI Global Scientific Publishing, vol. 13(2), pages 1-19, August.
    13. Alaa Alden Al Mohamed & Sobhi Al Mohamed, 2023. "Application of fuzzy group decision-making selecting green supplier: a case study of the manufacture of natural laurel soap," Future Business Journal, Springer, vol. 9(1), pages 1-20, December.
    14. Taiba Zahid & Fouzia Gillani & Usman Ghafoor & Muhammad Raheel Bhutta, 2022. "Synchromodal Transportation Analysis of the One-Belt-One-Road Initiative Based on a Bi-Objective Mathematical Model," Sustainability, MDPI, vol. 14(6), pages 1-14, March.
    15. Fadda, Edoardo & Manerba, Daniele & Cabodi, Gianpiero & Camurati, Paolo Enrico & Tadei, Roberto, 2021. "Comparative analysis of models and performance indicators for optimal service facility location," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 145(C).
    16. Chia-Nan Wang & Ngoc-Ai-Thy Nguyen & Thanh-Tuan Dang, 2023. "Sustainable Evaluation of Major Third-Party Logistics Providers: A Framework of an MCDM-Based Entropy Objective Weighting Method," Mathematics, MDPI, vol. 11(19), pages 1-27, October.
    17. Tian, Ran & Chang, Longlong & Sun, Zhihui & Zhao, Guanglu & Lu, Xin, 2025. "PTB: A deep reinforcement learning method for flexible logistics service combination problem with spatial-temporal constraint," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 195(C).
    18. Herweg, Fabian, 2013. "The expectation-based loss-averse newsvendor," Economics Letters, Elsevier, vol. 120(3), pages 429-432.
    19. Miguel Reyna-Castillo & Alejandro Santiago & Salvador Ibarra Martínez & José Antonio Castán Rocha, 2022. "Social Sustainability and Resilience in Supply Chains of Latin America on COVID-19 Times: Classification Using Evolutionary Fuzzy Knowledge," Mathematics, MDPI, vol. 10(14), pages 1-18, July.
    20. Marcel Rolf Pfeifer, 2021. "Human Resources during COVID-19: A Monthly Survey on Mental Health and Working Attitudes of Czech Employees and Managers during the Year 2020," Sustainability, MDPI, vol. 13(18), pages 1-20, September.

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jsusta:v:14:y:2022:i:4:p:2408-:d:753699. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.