IDEAS home Printed from https://ideas.repec.org/a/spr/joinma/v30y2019i5d10.1007_s10845-017-1383-6.html
   My bibliography  Save this article

Optimal control model for finite capacity continuous MRP with deteriorating items

Author

Listed:
  • Alireza Pooya

    (Ferdowsi University of Mashhad)

  • Morteza Pakdaman

    (Climatological Research Institute)

Abstract

A general model for continuous material requirements planning problem is proposed which contains of reworking of returned items along with deterioration of items. In the proposed model there are separated stocks for manufactured, returned and reworked items and also it is possible to consider returned items from both inventories of manufactured and reworked items. A general finite time linear quadratic optimal control problem is presented to attain the goal values for inventories, demands and productions. The goal values for inventories, demands and production can be considered as the capacity of stocks, scheduled demand and capacity of transportation respectively. Since the time is considered as a continuous parameter, the carrying cost of production process is more real than the periodic approach wherein time is considered as a discrete parameter. Finally a solution method is presented and numerical simulations are provided to validate the approach.

Suggested Citation

  • Alireza Pooya & Morteza Pakdaman, 2019. "Optimal control model for finite capacity continuous MRP with deteriorating items," Journal of Intelligent Manufacturing, Springer, vol. 30(5), pages 2203-2215, June.
    • Handle: RePEc:spr:joinma:v:30:y:2019:i:5:d:10.1007_s10845-017-1383-6
    DOI: 10.1007/s10845-017-1383-6
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s10845-017-1383-6
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s10845-017-1383-6?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Tommaso Rossi & Rossella Pozzi & Margherita Pero & Roberto Cigolini, 2017. "Improving production planning through finite-capacity MRP," International Journal of Production Research, Taylor & Francis Journals, vol. 55(2), pages 377-391, January.
    2. Benyaphorn Paopongchuang & Pisal Yenradee, 2014. "Finite capacity material requirement planning with supplier constraints," International Journal of Industrial and Systems Engineering, Inderscience Enterprises Ltd, vol. 17(3), pages 350-375.
    3. Vercraene, Samuel & Gayon, Jean-Philippe, 2013. "Optimal control of a production-inventory system with productreturns," International Journal of Production Economics, Elsevier, vol. 142(2), pages 302-310.
    4. Abdelhak Mezghiche & Mustapha Moulaï & Lotfi Tadj, 2015. "Model Predictive Control of a Forecasting Production System with Deteriorating Items," International Journal of Operations Research and Information Systems (IJORIS), IGI Global, vol. 6(4), pages 19-37, October.
    5. A. Foul & L. Tadj, 2007. "Optimal control of a hybrid periodic-review production inventory system with disposal," International Journal of Operational Research, Inderscience Enterprises Ltd, vol. 2(4), pages 481-494.
    6. Manuel Díaz-Madroñero & Josefa Mula & Mariano Jiménez & David Peidro, 2017. "A rolling horizon approach for material requirement planning under fuzzy lead times," International Journal of Production Research, Taylor & Francis Journals, vol. 55(8), pages 2197-2211, April.
    7. Hosseini, Seyedmohsen & Barker, Kash, 2016. "A Bayesian network model for resilience-based supplier selection," International Journal of Production Economics, Elsevier, vol. 180(C), pages 68-87.
    8. Jan Riezebos & Stuart X. Zhu, 2015. "MRP Planned Orders in a Multiple-Supplier Environment with Differing Lead Times," Production and Operations Management, Production and Operations Management Society, vol. 24(6), pages 883-895, June.
    9. Segerstedt, Anders, 2017. "Cover-Time Planning/Takt Planning: A technique for materials requirement and production planning," International Journal of Production Economics, Elsevier, vol. 194(C), pages 25-31.
    10. Milne, R. John & Mahapatra, Santosh & Wang, Chi-Tai, 2015. "Optimizing planned lead times for enhancing performance of MRP systems," International Journal of Production Economics, Elsevier, vol. 167(C), pages 220-231.
    11. Yun Sun & Yuanguo Zhu, 2017. "Bang–bang property for an uncertain saddle point problem," Journal of Intelligent Manufacturing, Springer, vol. 28(3), pages 605-613, March.
    12. Lakdere Benkherouf & Konstantina Skouri & Ioannis Konstantaras, 2016. "Optimal Control of Production, Remanufacturing and Refurbishing Activities in a Finite Planning Horizon Inventory System," Journal of Optimization Theory and Applications, Springer, vol. 168(2), pages 677-698, February.
    13. Grubbström, Robert W. & Tang, Ou, 2012. "The space of solution alternatives in the optimal lotsizing problem for general assembly systems applying MRP theory," International Journal of Production Economics, Elsevier, vol. 140(2), pages 765-777.
    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. Afshin Shariat & Zahra Hosseinnejad & Alireza Pooya, 2024. "Using the optimal control technique in facilities sharing to increased units’ efficiency," OPSEARCH, Springer;Operational Research Society of India, vol. 61(2), pages 741-761, June.

    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. Alireza Pooya & Morteza Pakdaman & Lotfi Tadj, 2019. "Exact and approximate solution for optimal inventory control of two-stock with reworking and forecasting of demand," Operational Research, Springer, vol. 19(2), pages 333-346, June.
    2. Sagawa, Juliana Keiko & Mušič, Gašper, 2019. "Towards the use of bond graphs for manufacturing control: Design of controllers," International Journal of Production Economics, Elsevier, vol. 214(C), pages 53-72.
    3. Qazi, Abroon & Dickson, Alex & Quigley, John & Gaudenzi, Barbara, 2018. "Supply chain risk network management: A Bayesian belief network and expected utility based approach for managing supply chain risks," International Journal of Production Economics, Elsevier, vol. 196(C), pages 24-42.
    4. Lin, Edward M.H. & Sun, Edward W. & Yu, Min-Teh, 2020. "Behavioral data-driven analysis with Bayesian method for risk management of financial services," International Journal of Production Economics, Elsevier, vol. 228(C).
    5. Fangzhong Qi & Leilei Zhang & Kexiang Zhuo & Xiuyan Ma, 2022. "Early Warning for Manufacturing Supply Chain Resilience Based on Improved Grey Prediction Model," Sustainability, MDPI, vol. 14(20), pages 1-16, October.
    6. Antonio Zavala-Alcívar & María-José Verdecho & Juan-José Alfaro-Saiz, 2020. "A Conceptual Framework to Manage Resilience and Increase Sustainability in the Supply Chain," Sustainability, MDPI, vol. 12(16), pages 1-38, August.
    7. Michail Tsagris, 2021. "A New Scalable Bayesian Network Learning Algorithm with Applications to Economics," Computational Economics, Springer;Society for Computational Economics, vol. 57(1), pages 341-367, January.
    8. De Iuliis, Melissa & Kammouh, Omar & Cimellaro, Gian Paolo & Tesfamariam, Solomon, 2021. "Quantifying restoration time of power and telecommunication lifelines after earthquakes using Bayesian belief network model," Reliability Engineering and System Safety, Elsevier, vol. 208(C).
    9. Amin Mahmoudi & Saad Ahmed Javed, 2022. "Probabilistic Approach to Multi-Stage Supplier Evaluation: Confidence Level Measurement in Ordinal Priority Approach," Group Decision and Negotiation, Springer, vol. 31(5), pages 1051-1096, October.
    10. Ahmadi, Somayeh & Saboohi, Yadollah & Vakili, Ali, 2021. "Frameworks, quantitative indicators, characters, and modeling approaches to analysis of energy system resilience: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 144(C).
    11. Hu, Shaolong & Dong, Zhijie Sasha, 2019. "Supplier selection and pre-positioning strategy in humanitarian relief," Omega, Elsevier, vol. 83(C), pages 287-298.
    12. Riezebos, Jan & Zhu, Stuart X., 2020. "Inventory control with seasonality of lead times," Omega, Elsevier, vol. 92(C).
    13. Zhu, Stuart X., 2015. "Analysis of dual sourcing strategies under supply disruptions," International Journal of Production Economics, Elsevier, vol. 170(PA), pages 191-203.
    14. Guo, Yan & Yu, Xinning & Zhou, Caifeng & Lyu, Gaoyan, 2021. "Government subsidies for preventing supply disruption when the supplier has an outside option under competition," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 147(C).
    15. Juan Pablo Usuga Cadavid & Samir Lamouri & Bernard Grabot & Robert Pellerin & Arnaud Fortin, 2020. "Machine learning applied in production planning and control: a state-of-the-art in the era of industry 4.0," Journal of Intelligent Manufacturing, Springer, vol. 31(6), pages 1531-1558, August.
    16. HOSSAIN, Niamat Ullah Ibne & Amrani, Safae El & Jaradat, Raed & Marufuzzaman, Mohammad & Buchanan, Randy & Rinaudo, Christina & Hamilton, Michael, 2020. "Modeling and assessing interdependencies between critical infrastructures using Bayesian network: A case study of inland waterway port and surrounding supply chain network," Reliability Engineering and System Safety, Elsevier, vol. 198(C).
    17. Ahmed Mohammed & Irina Harris & Anthony Soroka & Mohamed Naim & Tim Ramjaun & Morteza Yazdani, 2021. "Gresilient supplier assessment and order allocation planning," Annals of Operations Research, Springer, vol. 296(1), pages 335-362, January.
    18. Michail Tsagris, 2022. "The FEDHC Bayesian Network Learning Algorithm," Mathematics, MDPI, vol. 10(15), pages 1-28, July.
    19. Seyedmohsen Hosseini & Dmitry Ivanov, 2022. "A new resilience measure for supply networks with the ripple effect considerations: a Bayesian network approach," Annals of Operations Research, Springer, vol. 319(1), pages 581-607, December.
    20. Corinne Curt & Jean‐Marc Tacnet, 2018. "Resilience of Critical Infrastructures: Review and Analysis of Current Approaches," Risk Analysis, John Wiley & Sons, vol. 38(11), pages 2441-2458, November.

    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:spr:joinma:v:30:y:2019:i:5:d:10.1007_s10845-017-1383-6. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.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.