IDEAS home Printed from https://ideas.repec.org/a/gam/jlogis/v9y2025i2p63-d1663873.html
   My bibliography  Save this article

Optimizing Petroleum Products Distribution Centers Using GFA and AnyLogistix Simulation: A Case Study

Author

Listed:
  • Moqbel S. Jaffal

    (Laboratory of Applied Mechanics and Materials Production (LA2MP), National School of Engineers of Sfax (ENIS), BP. 1173—Route de Soukra (Boîte Postale), P.O. Box 1173, Sfax 3038, Tunisia)

  • Amjad B. Abdulghafour

    (Department of Production Engineering and Metallurgy, University of Technology, Baghdad 10066, Iraq)

  • Omar Ayadi

    (Laboratory of Applied Mechanics and Materials Production (LA2MP), National School of Engineers of Sfax (ENIS), BP. 1173—Route de Soukra (Boîte Postale), P.O. Box 1173, Sfax 3038, Tunisia)

  • Faouzi Masmoudi

    (Laboratory of Applied Mechanics and Materials Production (LA2MP), National School of Engineers of Sfax (ENIS), BP. 1173—Route de Soukra (Boîte Postale), P.O. Box 1173, Sfax 3038, Tunisia)

Abstract

Background : The Petroleum Products Distribution Company in Anbar Governorate is responsible for securing and distributing petroleum products to various sectors, including transportation, agriculture, industry, and households, through over 100 gas stations. The company has faced significant challenges due to the destruction of its infrastructure caused by past conflicts. These challenges have necessitated strategic decisions to design an efficient distribution network. Methods: This study aimed to assist the company in selecting the optimal location for a distribution center by evaluating four potential locations. Three of the proposed locations were suggested by the company: Ramadi, Habbaniyah, and Haqlaniyah. The fourth location, referred to as the GFA DC location, was determined through a greenfield analysis (GFA) experiment using AnyLogistix software (version 3.2.1. PLE) ALX. The simulation experiment in ALX was conducted using product data, fuel station locations, order quantities, distribution center data, and transportation and emissions data. Results : The simulation results, taking into account both practical and regulatory constraints, indicated that the Ramadi location was the most suitable for establishing the new distribution center. Conclusions : Based on the analysis, the study concluded that the Ramadi location was the optimal site for building the petroleum products distribution center in Anbar Governorate, offering a solution that aligns with the company’s goals of improving distribution efficiency and overcoming existing logistical challenges.

Suggested Citation

  • Moqbel S. Jaffal & Amjad B. Abdulghafour & Omar Ayadi & Faouzi Masmoudi, 2025. "Optimizing Petroleum Products Distribution Centers Using GFA and AnyLogistix Simulation: A Case Study," Logistics, MDPI, vol. 9(2), pages 1-15, May.
    • Handle: RePEc:gam:jlogis:v:9:y:2025:i:2:p:63-:d:1663873
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2305-6290/9/2/63/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2305-6290/9/2/63/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Kazemi, Yasaman & Szmerekovsky, Joseph, 2015. "Modeling downstream petroleum supply chain: The importance of multi-mode transportation to strategic planning," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 83(C), pages 111-125.
    2. Wang, Ge & Huang, Samuel H. & Dismukes, John P., 2004. "Product-driven supply chain selection using integrated multi-criteria decision-making methodology," International Journal of Production Economics, Elsevier, vol. 91(1), pages 1-15, September.
    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. Huang, Samuel H. & Keskar, Harshal, 2007. "Comprehensive and configurable metrics for supplier selection," International Journal of Production Economics, Elsevier, vol. 105(2), pages 510-523, February.
    2. Farahani, Mohsen & Rahmani, Donya, 2017. "Production and distribution planning in petroleum supply chains regarding the impacts of gas injection and swap," Energy, Elsevier, vol. 141(C), pages 991-1003.
    3. Ilkka Sillanpää & Sebastian Sillanpää, 2014. "Supply Chain Strategy: Empirical Case Study in Europe and Asia," Management, University of Primorska, Faculty of Management Koper, vol. 9(2), pages 95-115.
    4. Fatemeh Vardan & Seyed Mohammad Hassan Hosseini, 2025. "A bi-objective model for designing a green closed-loop supply chain network in a petroleum complex considering transportation constraints: a case study," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 16(3), pages 1020-1039, March.
    5. Hayk Manucharyan, 2020. "Supplier selection in emerging market economies: a discrete choice analysis," Working Papers 2020-11, Faculty of Economic Sciences, University of Warsaw.
    6. Herbert Dawid & Reinhold Decker & Thomas Hermann & Hermann Jahnke & Wilhelm Klat & Rolf König & Christian Stummer, 2017. "Management science in the era of smart consumer products: challenges and research perspectives," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 25(1), pages 203-230, March.
    7. Kannan Govindan & R. Sivakumar, 2016. "Green supplier selection and order allocation in a low-carbon paper industry: integrated multi-criteria heterogeneous decision-making and multi-objective linear programming approaches," Annals of Operations Research, Springer, vol. 238(1), pages 243-276, March.
    8. Reza Farzipoor Saen, 2009. "A decision model for ranking suppliers in the presence of cardinal and ordinal data, weight restrictions, and nondiscretionary factors," Annals of Operations Research, Springer, vol. 172(1), pages 177-192, November.
    9. Chen, Yan & Huang, Zhenhua & Ai, Hongshan & Guo, Xingkun & Luo, Fan, 2021. "The Impact of GIS/GPS Network Information Systems on the Logistics Distribution Cost of Tobacco Enterprises," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 149(C).
    10. Chan, Felix T.S. & Kumar, Niraj, 2007. "Global supplier development considering risk factors using fuzzy extended AHP-based approach," Omega, Elsevier, vol. 35(4), pages 417-431, August.
    11. Ramanathan, Usha, 2013. "Aligning supply chain collaboration using Analytic Hierarchy Process," Omega, Elsevier, vol. 41(2), pages 431-440.
    12. Carmona-Benítez, Rafael Bernardo & Cruz, Héctor, 2023. "A multiproduct gasoline supply chain with product standardization and postponement strategy," Socio-Economic Planning Sciences, Elsevier, vol. 88(C).
    13. Emenike, Scholastica N. & Falcone, Gioia, 2020. "A review on energy supply chain resilience through optimization," Renewable and Sustainable Energy Reviews, Elsevier, vol. 134(C).
    14. R-H Lin, 2009. "Potential use of FP-growth algorithm for identifying competitive suppliers in SCM," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 60(8), pages 1135-1141, August.
    15. Hu, Kuo-Jen & Yu, Vincent F., 2016. "An integrated approach for the electronic contract manufacturer selection problem," Omega, Elsevier, vol. 62(C), pages 68-81.
    16. Scott, James A. & Ho, William & Dey, Prasanta K., 2013. "Strategic sourcing in the UK bioenergy industry," International Journal of Production Economics, Elsevier, vol. 146(2), pages 478-490.
    17. Kelle, Peter & Miller, Pamela A. & Akbulut, Asli Y., 2007. "Coordinating ordering/shipment policy for buyer and supplier: Numerical and empirical analysis of influencing factors," International Journal of Production Economics, Elsevier, vol. 108(1-2), pages 100-110, July.
    18. Ustun, Ozden & DemI[dot above]rtas, Ezgi Aktar, 2008. "An integrated multi-objective decision-making process for multi-period lot-sizing with supplier selection," Omega, Elsevier, vol. 36(4), pages 509-521, August.
    19. Brandenburg, Marcus, 2017. "A hybrid approach to configure eco-efficient supply chains under consideration of performance and risk aspects," Omega, Elsevier, vol. 70(C), pages 58-76.
    20. Bayazit, Ozden & Karpak, Birsen, 2007. "An analytical network process-based framework for successful total quality management (TQM): An assessment of Turkish manufacturing industry readiness," International Journal of Production Economics, Elsevier, vol. 105(1), pages 79-96, January.

    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:jlogis:v:9:y:2025:i:2:p:63-:d:1663873. 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.