IDEAS home Printed from https://ideas.repec.org/a/spr/opsear/v57y2020i3d10.1007_s12597-020-00460-x.html
   My bibliography  Save this article

Investigations into control strategies of supply chain planning models: a case study

Author

Listed:
  • T. V. S. R. K. Prasad

    (ST.MARY’S GROUP OF INSTITUTIONS, GUNTUR)

  • Kolla Srinivas

    (R.V.R&J.C. College of Engineering)

  • C. Srinivas

    (R.V.R&J.C. College of Engineering)

Abstract

In the past, several frameworks and models have been developed in the literatures that addressed the problems and issues of logistics in a supply chain management. In the literature, only few number of variables are taken into consideration in obtaining the solution of the supply chain and most of the research is done on decentralized control strategy only. Such kind of analysis may not give the appropriate solution to the manufacturer among different alternatives. Hence it is necessary to investigate all the variables that affect the performance of the supply chain under different control strategies. The aim of the present work is to compare the centralized and decentralized supply chains to find out which type of supply chain is more advantageous in terms of cost. Two mathematical models were proposed, one for decentralized supply chain and the other for centralized supply chain for comparing the total cost of the two supply chains. In the present work to implement decentralized supply chain an agent based methodology and for centralized supply chain model a linear program model has been used. The author proposed a novel centralized supply chain which considers the same costs and capacities as were considered in the decentralized supply chain. The only difference considered here between centralized and decentralized supply chains is the amount of information sharing. The contribution of this paper is to formulate the centralized and decentralized multi-product multi-period supply chain models and to implement both the models in GAMS software and to obtain the results using NEOS optimization web site. In this paper, 1728 variables for distribution agent and 576 variables for production agent and 192 linking variables, totally 2496 variables are considered which enabled to study the complexity and intricacies of the supply chain. From the results, it was found that a saving of Rs. 4,72,44,400 is possible, if the domestic pump industry considered in the paper follows centralized production–distribution planning. The month-wise production quantity, distribution quantities from factory to distribution centre and from distribution centre to customer, month-wise inventory quantities to minimize the total cost are also obtained.

Suggested Citation

  • T. V. S. R. K. Prasad & Kolla Srinivas & C. Srinivas, 2020. "Investigations into control strategies of supply chain planning models: a case study," OPSEARCH, Springer;Operational Research Society of India, vol. 57(3), pages 874-907, September.
  • Handle: RePEc:spr:opsear:v:57:y:2020:i:3:d:10.1007_s12597-020-00460-x
    DOI: 10.1007/s12597-020-00460-x
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s12597-020-00460-x
    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/s12597-020-00460-x?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. Ji Seong Noh & Jong Soo Kim & Biswajit Sarkar, 2019. "Stochastic joint replenishment problem with quantity discounts and minimum order constraints," Operational Research, Springer, vol. 19(1), pages 151-178, March.
    2. Jayaraman, Vaidyanathan & Ross, Anthony, 2003. "A simulated annealing methodology to distribution network design and management," European Journal of Operational Research, Elsevier, vol. 144(3), pages 629-645, February.
    3. Duan, Qinglin & Warren Liao, T., 2013. "Optimization of replenishment policies for decentralized and centralized capacitated supply chains under various demands," International Journal of Production Economics, Elsevier, vol. 142(1), pages 194-204.
    4. Mitali Sarkar & Sungjun Kim & Jihed Jemai & Baishakhi Ganguly & Biswajit Sarkar, 2019. "An Application of Time-Dependent Holding Costs and System Reliability in a Multi-Item Sustainable Economic Energy Efficient Reliable Manufacturing System," Energies, MDPI, vol. 12(15), pages 1-19, July.
    5. Hau L. Lee & V. Padmanabhan & Seungjin Whang, 2004. "Comments on "Information Distortion in a Supply Chain: The Bullwhip Effect"," Management Science, INFORMS, vol. 50(12_supple), pages 1887-1893, December.
    6. Erenguc, S. Selcuk & Simpson, N. C. & Vakharia, Asoo J., 1999. "Integrated production/distribution planning in supply chains: An invited review," European Journal of Operational Research, Elsevier, vol. 115(2), pages 219-236, June.
    7. Hau L. Lee & V. Padmanabhan & Seungjin Whang, 2004. "Information Distortion in a Supply Chain: The Bullwhip Effect," Management Science, INFORMS, vol. 50(12_supple), pages 1875-1886, December.
    8. T. William Chien & Anantaram Balakrishnan & Richard T. Wong, 1989. "An Integrated Inventory Allocation and Vehicle Routing Problem," Transportation Science, INFORMS, vol. 23(2), pages 67-76, May.
    9. Albrecht, Martin & Stadtler, Hartmut, 2015. "Coordinating decentralized linear programs by exchange of primal information," European Journal of Operational Research, Elsevier, vol. 247(3), pages 788-796.
    10. Sarkar, Biswajit & Guchhait, Rekha & Sarkar, Mitali & Cárdenas-Barrón, Leopoldo Eduardo, 2019. "How does an industry manage the optimum cash flow within a smart production system with the carbon footprint and carbon emission under logistics framework?," International Journal of Production Economics, Elsevier, vol. 213(C), pages 243-257.
    11. Ullah, Mehran & Sarkar, Biswajit, 2020. "Recovery-channel selection in a hybrid manufacturing-remanufacturing production model with RFID and product quality," International Journal of Production Economics, Elsevier, vol. 219(C), pages 360-374.
    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. Javier Arturo Orjuela-Castro & Juan Pablo Orejuela-Cabrera & Wilson Adarme-Jaimes, 2022. "Multi-objective model for perishable food logistics networks design considering availability and access," OPSEARCH, Springer;Operational Research Society of India, vol. 59(4), pages 1244-1270, December.

    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. Wu, Chengfeng & Liu, Xin & Li, Annan, 2021. "A loss-averse retailer–supplier supply chain model under trade credit in a supplier-Stackelberg game," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 182(C), pages 353-365.
    2. Wang, Zhaodong & Wang, Xin & Ouyang, Yanfeng, 2015. "Bounded growth of the bullwhip effect under a class of nonlinear ordering policies," European Journal of Operational Research, Elsevier, vol. 247(1), pages 72-82.
    3. Zhang, Xiaolong & Burke, Gerard J., 2011. "Analysis of compound bullwhip effect causes," European Journal of Operational Research, Elsevier, vol. 210(3), pages 514-526, May.
    4. Seitz, Alexander & Grunow, Martin & Akkerman, Renzo, 2020. "Data driven supply allocation to individual customers considering forecast bias," International Journal of Production Economics, Elsevier, vol. 227(C).
    5. Darwish, M.A. & Odah, O.M., 2010. "Vendor managed inventory model for single-vendor multi-retailer supply chains," European Journal of Operational Research, Elsevier, vol. 204(3), pages 473-484, August.
    6. Chong, Alain Yee-Loong & Zhou, Li, 2014. "Demand chain management: Relationships between external antecedents, web-based integration and service innovation performance," International Journal of Production Economics, Elsevier, vol. 154(C), pages 48-58.
    7. Abhijit Baidya, 2019. "Stochastic supply chain, transportation models: implementations and benefits," OPSEARCH, Springer;Operational Research Society of India, vol. 56(2), pages 432-476, June.
    8. Ding, Huiping & Guo, Baochun & Liu, Zhishuo, 2011. "Information sharing and profit allotment based on supply chain cooperation," International Journal of Production Economics, Elsevier, vol. 133(1), pages 70-79, September.
    9. Pedro Domingos Antoniolli, 2016. "Information Technology Framework for Pharmaceutical Supply Chain Demand Management: a Brazilian Case Study," Brazilian Business Review, Fucape Business School, vol. 13(2), pages 27-55, March.
    10. Patrick R. Burgess & Funlade T. Sunmola, 2022. "Exploring Attractive Quality Requirements for Short Food Supply Chain Digital Platforms," International Journal of Information Systems and Supply Chain Management (IJISSCM), IGI Global, vol. 15(1), pages 1-24, January.
    11. Ying Rong & Lawrence V. Snyder & Zuo‐Jun Max Shen, 2017. "Bullwhip and reverse bullwhip effects under the rationing game," Naval Research Logistics (NRL), John Wiley & Sons, vol. 64(3), pages 203-216, April.
    12. Iman Kazemian & Samin Aref, 2016. "Multi-echelon Supply Chain Flexibility Enhancement Through Detecting Bottlenecks," Global Journal of Flexible Systems Management, Springer;Global Institute of Flexible Systems Management, vol. 17(4), pages 357-372, December.
    13. Alexander Seitz & Hans Ehm & Renzo Akkerman & Sarah Osman, 2016. "A robust supply chain planning framework for revenue management in the semiconductor industry," Journal of Revenue and Pricing Management, Palgrave Macmillan, vol. 15(6), pages 523-533, December.
    14. Zormpas, Dimitrios, 2020. "Investments under vertical relations and agency conflicts: A real options approach," International Review of Economics & Finance, Elsevier, vol. 70(C), pages 273-287.
    15. Nowak, Thomas & Hofer, Vera, 2014. "On stabilizing volatile product returns," European Journal of Operational Research, Elsevier, vol. 234(3), pages 701-708.
    16. repec:hrs:journl::y:2012:v:4:i:3:p:137-153 is not listed on IDEAS
    17. Taleizadeh, Ata Allah & Tafakkori, Keivan & Thaichon, Park, 2021. "Resilience toward supply disruptions: A stochastic inventory control model with partial backordering under the base stock policy," Journal of Retailing and Consumer Services, Elsevier, vol. 58(C).
    18. Woo, Donghyup & Suresh, Nallan C., 2022. "Voluntary agreements for sustainability, resource efficiency & firm performance under the supply chain cooperation policy in South Korea," International Journal of Production Economics, Elsevier, vol. 252(C).
    19. Sucky, Eric, 2009. "The bullwhip effect in supply chains--An overestimated problem?," International Journal of Production Economics, Elsevier, vol. 118(1), pages 311-322, March.
    20. T. V. S. R. K. Prasad & Kolla Srinivas & C. Srinivas, 2017. "Decentralized production–distribution planning in multi-echelon supply chain network using intelligent agents," OPSEARCH, Springer;Operational Research Society of India, vol. 54(2), pages 217-232, June.
    21. Iossifov, Plamen, 2014. "Cross-border production chains and business cycle co-movement between Central and Eastern European countries and euro area member states," Working Paper Series 1628, European Central Bank.

    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:opsear:v:57:y:2020:i:3:d:10.1007_s12597-020-00460-x. 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.