IDEAS home Printed from https://ideas.repec.org/a/gam/jmathe/v9y2021i5p568-d512173.html
   My bibliography  Save this article

Optimization and Simulation of Dynamic Performance of Production–Inventory Systems with Multivariable Controls

Author

Listed:
  • Huthaifa AL-Khazraji

    (Department of Control and System Engineering, University of Technology, Al-Wehda Neighborhood, Baghdad 10066, Iraq)

  • Colin Cole

    (School of Engineering and Technology, Central Queensland University, Bruce Highway, North Rockhampton, QLD 4702, Australia)

  • William Guo

    (School of Engineering and Technology, Central Queensland University, Bruce Highway, North Rockhampton, QLD 4702, Australia)

Abstract

The production–inventory system is a problem of multivariable input and multivariant output in mathematics. Selecting the best system control parameters is a crucial managerial decision to achieve and dynamically maintain an optimal performance in terms of balancing the order rate and stock level under dynamic influence of many factors affecting the system operations. The dynamic performance of the popular APIOBPCS model and the newly modified 2APIOBPCS model for optimal control of production–inventory systems is examined in the study. This examination is based on the leveled ground with a new simulation scheme that incorporates a designated multi-objective particle swarm optimization (MOPSO) algorithm into the simulation, which enables the optimal set of system control parameters to be selected for achieving the situational best possible performance of the production–inventory system under study. The dynamic performance is measured by the variance ratio between the order rate and the sales rate related to the bullwhip effect, and the integral of absolute error related to the inventory responsiveness in response to a random customer demand. Our simulation indicates that the 2APIOBPCS model performed better than or at least no worse than, and more robust than the APIOBPCS model under different conditions.

Suggested Citation

  • Huthaifa AL-Khazraji & Colin Cole & William Guo, 2021. "Optimization and Simulation of Dynamic Performance of Production–Inventory Systems with Multivariable Controls," Mathematics, MDPI, vol. 9(5), pages 1-13, March.
    • Handle: RePEc:gam:jmathe:v:9:y:2021:i:5:p:568-:d:512173
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2227-7390/9/5/568/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2227-7390/9/5/568/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Lin, J. & Naim, M.M. & Purvis, L. & Gosling, J., 2017. "The extension and exploitation of the inventory and order based production control system archetype from 1982 to 2015," International Journal of Production Economics, Elsevier, vol. 194(C), pages 135-152.
    2. A. Negahban & J.S. Smith, 2016. "The effect of supply and demand uncertainties on the optimal production and sales plans for new products," International Journal of Production Research, Taylor & Francis Journals, vol. 54(13), pages 3852-3869, July.
    3. Salvatore Cannella & Rosa G. González-Ramírez & Roberto Dominguez & Mónica A. López-Campos & Pablo A. Miranda, 2017. "Modelling and Simulation in Operations and Complex Supply Chains," Mathematical Problems in Engineering, Hindawi, vol. 2017, pages 1-3, January.
    4. Aggelogiannaki, Eleni & Sarimveis, Haralambos, 2008. "Design of a novel adaptive inventory control system based on the online identification of lead time," International Journal of Production Economics, Elsevier, vol. 114(2), pages 781-792, August.
    5. Dejonckheere, J. & Disney, S. M. & Lambrecht, M. R. & Towill, D. R., 2003. "Measuring and avoiding the bullwhip effect: A control theoretic approach," European Journal of Operational Research, Elsevier, vol. 147(3), pages 567-590, June.
    6. Zhou, Li & Naim, Mohamed M. & Ou Tang & Towill, Denis R., 2006. "Dynamic performance of a hybrid inventory system with a Kanban policy in remanufacturing process," Omega, Elsevier, vol. 34(6), pages 585-598, December.
    7. Wikner, Joakim & Naim, Mohamed M. & Spiegler, Virginia L.M. & Lin, Junyi, 2017. "IOBPCS based models and decoupling thinking," International Journal of Production Economics, Elsevier, vol. 194(C), pages 153-166.
    8. Herbert J. Vassian, 1955. "Application of Discrete Variable Servo Theory to Inventory Control," Operations Research, INFORMS, vol. 3(3), pages 272-282, August.
    9. Disney, S.M. & Towill, D.R., 2005. "Eliminating drift in inventory and order based production control systems," International Journal of Production Economics, Elsevier, vol. 93(1), pages 331-344, January.
    10. Mula, J. & Poler, R. & Garcia-Sabater, J.P. & Lario, F.C., 2006. "Models for production planning under uncertainty: A review," International Journal of Production Economics, Elsevier, vol. 103(1), pages 271-285, September.
    11. Holweg, Matthias & Disney, Stephen & Holmström, Jan & Småros, Johanna, 2005. "Supply Chain Collaboration:: Making Sense of the Strategy Continuum," European Management Journal, Elsevier, vol. 23(2), pages 170-181, April.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Dharamender Singh & Anurag Jayswal & Majed G. Alharbi & Ali Akbar Shaikh, 2021. "An Investigation of a Supply Chain Model for Co-Ordination of Finished Products and Raw Materials in a Production System under Different Situations," Sustainability, MDPI, vol. 13(22), pages 1-25, November.
    2. Péter Kováts & Róbert Skapinyecz, 2024. "A Combined Capacity Planning and Simulation Approach for the Optimization of AGV Systems in Complex Production Logistics Environments," Logistics, MDPI, vol. 8(4), pages 1-27, November.

    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. Lin, J. & Naim, M.M. & Purvis, L. & Gosling, J., 2017. "The extension and exploitation of the inventory and order based production control system archetype from 1982 to 2015," International Journal of Production Economics, Elsevier, vol. 194(C), pages 135-152.
    2. Lin, Junyi & Zhou, Li & Spiegler, Virginia L.M. & Naim, Mohamed M. & Syntetos, Aris, 2022. "Push or Pull? The impact of ordering policy choice on the dynamics of a hybrid closed-loop supply chain," European Journal of Operational Research, Elsevier, vol. 300(1), pages 282-295.
    3. Lin, Junyi & Huang, Hongfu & Li, Shanshan & Naim, Mohamed M., 2023. "On the dynamics of order pipeline inventory in a nonlinear order-up-to system," International Journal of Production Economics, Elsevier, vol. 266(C).
    4. Lin, Junyi & Naim, Mohamed M. & Spiegler, Virginia L.M., 2020. "Delivery time dynamics in an assemble-to-order inventory and order based production control system," International Journal of Production Economics, Elsevier, vol. 223(C).
    5. Ponte, Borja & Dominguez, Roberto & Cannella, Salvatore & Framinan, Jose M., 2022. "The implications of batching in the bullwhip effect and customer service of closed-loop supply chains," International Journal of Production Economics, Elsevier, vol. 244(C).
    6. Ponte, Borja & Framinan, Jose M. & Cannella, Salvatore & Dominguez, Roberto, 2020. "Quantifying the Bullwhip Effect in closed-loop supply chains: The interplay of information transparencies, return rates, and lead times," International Journal of Production Economics, Elsevier, vol. 230(C).
    7. Ponte, Borja & Costas, José & Puche, Julio & Pino, Raúl & de la Fuente, David, 2018. "The value of lead time reduction and stabilization: A comparison between traditional and collaborative supply chains," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 111(C), pages 165-185.
    8. Lina Tang & Taho Yang & Yiliu Tu & Yizhong Ma, 2021. "Supply chain information sharing under consideration of bullwhip effect and system robustness," Flexible Services and Manufacturing Journal, Springer, vol. 33(2), pages 337-380, June.
    9. Ponte, Borja & Cannella, Salvatore & Dominguez, Roberto & Naim, Mohamed M. & Syntetos, Aris A., 2021. "Quality grading of returns and the dynamics of remanufacturing," International Journal of Production Economics, Elsevier, vol. 236(C).
    10. Ma, Yungao & Wang, Nengmin & He, Zhengwen & Lu, Jizhou & Liang, Huigang, 2015. "Analysis of the bullwhip effect in two parallel supply chains with interacting price-sensitive demands," European Journal of Operational Research, Elsevier, vol. 243(3), pages 815-825.
    11. Disney, Stephen M. & Towill, Denis R. & Warburton, Roger D.H., 2006. "On the equivalence of control theoretic, differential, and difference equation approaches to modeling supply chains," International Journal of Production Economics, Elsevier, vol. 101(1), pages 194-208, May.
    12. Hosoda, Takamichi & Disney, Stephen M., 2018. "A unified theory of the dynamics of closed-loop supply chains," European Journal of Operational Research, Elsevier, vol. 269(1), pages 313-326.
    13. Zhou, Li & Naim, Mohamed M. & Disney, Stephen M., 2017. "The impact of product returns and remanufacturing uncertainties on the dynamic performance of a multi-echelon closed-loop supply chain," International Journal of Production Economics, Elsevier, vol. 183(PB), pages 487-502.
    14. A A Syntetos & J E Boylan & S M Disney, 2009. "Forecasting for inventory planning: a 50-year review," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 60(1), pages 149-160, May.
    15. Warburton, Roger D. H., 2004. "An exact analytical solution to the production inventory control problem," International Journal of Production Economics, Elsevier, vol. 92(1), pages 81-96, November.
    16. Lin, Junyi & Naim, Mohamed M. & Tang, Ou, 2024. "In-house or outsourcing? The impact of remanufacturing strategies on the dynamics of component remanufacturing systems under lifecycle demand and returns," European Journal of Operational Research, Elsevier, vol. 315(3), pages 965-979.
    17. Disney, S.M. & Farasyn, I. & Lambrecht, M. & Towill, D.R. & de Velde, W. Van, 2006. "Taming the bullwhip effect whilst watching customer service in a single supply chain echelon," European Journal of Operational Research, Elsevier, vol. 173(1), pages 151-172, August.
    18. Gaalman, Gerard & Disney, Stephen M., 2006. "State space investigation of the bullwhip problem with ARMA(1,1) demand processes," International Journal of Production Economics, Elsevier, vol. 104(2), pages 327-339, December.
    19. A. V. Thomas & Biswajit Mahanty, 2021. "Dynamic assessment of control system designs of information shared supply chain network experiencing supplier disruption," Operational Research, Springer, vol. 21(1), pages 425-451, March.
    20. Zhou, Yuxuan & Wang, Xun & Naim, Mohamed M. & Gosling, Jonathan, 2022. "A system dynamics archetype to mitigate rework effects in engineer-to-order supply chains," International Journal of Production Economics, Elsevier, vol. 250(C).

    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:jmathe:v:9:y:2021:i:5:p:568-:d:512173. 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.