IDEAS home Printed from https://ideas.repec.org/a/spr/joinma/v29y2018i6d10.1007_s10845-015-1172-z.html
   My bibliography  Save this article

An uncertain mathematical model to maximize profit of the defective goods supply chain by selecting appropriate suppliers

Author

Listed:
  • Salah Alden Ghasimi

    (Universiti Kebangsaan Malaysia
    Islamic Azad University, Sanandaj Branch)

  • Rizauddin Ramli

    (Universiti Kebangsaan Malaysia)

  • Nizaroyani Saibani

    (Universiti Kebangsaan Malaysia)

  • Khashayar Danesh Narooei

    (Universiti Kebangsaan Malaysia)

Abstract

This study presents an uncertain mathematical model for maximizing profit of the defective goods supply chain during uncertain situations by using selection of appropriate suppliers, just-in-time (JIT) logistic philosophy and minimizing total costs including costs of production, shipping, holding, defective goods, scrap goods, shortage in retailers. The selections of suppliers are based on three criteria, namely, quality, JIT delivery, and level of responsibility, which have important roles in the production of perfect goods by manufacturers. In each criterion, two kinds of indicators are considered by manufacturers. The first indicator is the importance of the weighted factor of each criterion for each manufacturer, and the second is weighted factor of each supplier with respect to each criterion. The proposed mathematical model with uncertain parameters and the probability of occurring in various scenarios is investigated. The model is studied in ten scenarios and the average amount is calculated. The mentioned mathematical model is solved by the averages of the parameters using CPLEX.12 solver and Expert Choice software. The findings of the model are maximum profit, amounts of economic production quantity, defective goods, scrap goods, and amounts of products that should be exchanged among the nodes of the supply chain. To achieve maximum benefit, the model can select the appropriate suppliers. The results obtained demonstrate the validity and efficiency of the proposed uncertain mathematical model.

Suggested Citation

  • Salah Alden Ghasimi & Rizauddin Ramli & Nizaroyani Saibani & Khashayar Danesh Narooei, 2018. "An uncertain mathematical model to maximize profit of the defective goods supply chain by selecting appropriate suppliers," Journal of Intelligent Manufacturing, Springer, vol. 29(6), pages 1219-1234, August.
  • Handle: RePEc:spr:joinma:v:29:y:2018:i:6:d:10.1007_s10845-015-1172-z
    DOI: 10.1007/s10845-015-1172-z
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s10845-015-1172-z
    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/s10845-015-1172-z?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. Liao, Zhiying & Rittscher, Jens, 2007. "A multi-objective supplier selection model under stochastic demand conditions," International Journal of Production Economics, Elsevier, vol. 105(1), pages 150-159, January.
    2. Liu, Fuh-Hwa Franklin & Hai, Hui Lin, 2005. "The voting analytic hierarchy process method for selecting supplier," International Journal of Production Economics, Elsevier, vol. 97(3), pages 308-317, September.
    3. Vanteddu, Gangaraju & Chinnam, Ratna Babu & Gushikin, Oleg, 2011. "Supply chain focus dependent supplier selection problem," International Journal of Production Economics, Elsevier, vol. 129(1), pages 204-216, January.
    4. Chen, Chen-Tung & Lin, Ching-Torng & Huang, Sue-Fn, 2006. "A fuzzy approach for supplier evaluation and selection in supply chain management," International Journal of Production Economics, Elsevier, vol. 102(2), pages 289-301, August.
    5. Kawtummachai, Ruengsak & Van Hop, Nguyen, 2005. "Order allocation in a multiple-supplier environment," International Journal of Production Economics, Elsevier, vol. 93(1), pages 231-238, January.
    6. Oded Berman & Qian Wang, 2006. "Inbound Logistic Planning: Minimizing Transportation and Inventory Cost," Transportation Science, INFORMS, vol. 40(3), pages 287-299, August.
    7. Alex X. Zhang, 1997. "Demand Fulfillment Rates In An Assembleto‐ Order System With Multiple Products And Dependent Demands," Production and Operations Management, Production and Operations Management Society, vol. 6(3), pages 309-324, September.
    8. Amid, A. & Ghodsypour, S.H. & O'Brien, C., 2006. "Fuzzy multiobjective linear model for supplier selection in a supply chain," International Journal of Production Economics, Elsevier, vol. 104(2), pages 394-407, December.
    9. Amid, A. & Ghodsypour, S.H. & O'Brien, C., 2011. "A weighted max-min model for fuzzy multi-objective supplier selection in a supply chain," International Journal of Production Economics, Elsevier, vol. 131(1), pages 139-145, May.
    10. Ghodsypour, S. H. & O'Brien, C., 2001. "The total cost of logistics in supplier selection, under conditions of multiple sourcing, multiple criteria and capacity constraint," International Journal of Production Economics, Elsevier, vol. 73(1), pages 15-27, August.
    11. Weber, Charles A. & Current, John R. & Desai, Anand, 1998. "Non-cooperative negotiation strategies for vendor selection," European Journal of Operational Research, Elsevier, vol. 108(1), pages 208-223, July.
    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. Ho, William & Xu, Xiaowei & Dey, Prasanta K., 2010. "Multi-criteria decision making approaches for supplier evaluation and selection: A literature review," European Journal of Operational Research, Elsevier, vol. 202(1), pages 16-24, April.
    2. Scott, James & Ho, William & Dey, Prasanta K. & Talluri, Srinivas, 2015. "A decision support system for supplier selection and order allocation in stochastic, multi-stakeholder and multi-criteria environments," International Journal of Production Economics, Elsevier, vol. 166(C), pages 226-237.
    3. Lin, Rong-Ho, 2012. "An integrated model for supplier selection under a fuzzy situation," International Journal of Production Economics, Elsevier, vol. 138(1), pages 55-61.
    4. Woo, Hong Seng & Saghiri, Soroosh, 2011. "Order assignment considering buyer, third-party logistics provider, and suppliers," International Journal of Production Economics, Elsevier, vol. 130(2), pages 144-152, April.
    5. Aly Owida & P.J. Byrne & Cathal Heavey & Paul Blake & Khaled S. El-Kilany, 2016. "A simulation based continuous improvement approach for manufacturing based field repair service contracting," International Journal of Production Research, Taylor & Francis Journals, vol. 54(21), pages 6458-6477, November.
    6. Ashoke Kumar Bera & Dipak Kumar Jana & Debamalya Banerjee & Titas Nandy, 2021. "A Two-Phase Multi-criteria Fuzzy Group Decision Making Approach for Supplier Evaluation and Order Allocation Considering Multi-objective, Multi-product and Multi-period," Annals of Data Science, Springer, vol. 8(3), pages 577-601, September.
    7. García Alcaraz Jorge Luis & Alvarado Iniesta Alejandro & Maldonado Macías Aidé Araceli, 2013. "Selección de proveedores basada en análisis dimensional," Contaduría y Administración, Accounting and Management, vol. 58(3), pages 249-278, julio-sep.
    8. Bottani, Eleonora & Rizzi, Antonio, 2008. "An adapted multi-criteria approach to suppliers and products selection--An application oriented to lead-time reduction," International Journal of Production Economics, Elsevier, vol. 111(2), pages 763-781, February.
    9. Mohammaditabar, Davood & Ghodsypour, Seyed Hassan & Hafezalkotob, Ashkan, 2016. "A game theoretic analysis in capacity-constrained supplier-selection and cooperation by considering the total supply chain inventory costs," International Journal of Production Economics, Elsevier, vol. 181(PA), pages 87-97.
    10. Mohammed, Ahmed & Harris, Irina & Govindan, Kannan, 2019. "A hybrid MCDM-FMOO approach for sustainable supplier selection and order allocation," International Journal of Production Economics, Elsevier, vol. 217(C), pages 171-184.
    11. Hosseininasab, Amin & Ahmadi, Abbas, 2015. "Selecting a supplier portfolio with value, development, and risk consideration," European Journal of Operational Research, Elsevier, vol. 245(1), pages 146-156.
    12. Chang, Liu & Ouzrout, Yacine & Nongaillard, Antoine & Bouras, Abdelaziz & Jiliu, Zhou, 2014. "Multi-criteria decision making based on trust and reputation in supply chain," International Journal of Production Economics, Elsevier, vol. 147(PB), pages 362-372.
    13. Saen, Reza Farzipoor, 2007. "Suppliers selection in the presence of both cardinal and ordinal data," European Journal of Operational Research, Elsevier, vol. 183(2), pages 741-747, December.
    14. Rezaei, Jafar & Davoodi, Mansoor, 2011. "Multi-objective models for lot-sizing with supplier selection," International Journal of Production Economics, Elsevier, vol. 130(1), pages 77-86, March.
    15. Araz, Ceyhun & Ozkarahan, Irem, 2007. "Supplier evaluation and management system for strategic sourcing based on a new multicriteria sorting procedure," International Journal of Production Economics, Elsevier, vol. 106(2), pages 585-606, April.
    16. Mukherjee, Krishnendu, 2014. "Supplier selection criteria and methods: past, present and future," MPRA Paper 60079, University Library of Munich, Germany.
    17. Chen, Lisa Y. & Wang, Tien-Chin, 2009. "Optimizing partners' choice in IS/IT outsourcing projects: The strategic decision of fuzzy VIKOR," International Journal of Production Economics, Elsevier, vol. 120(1), pages 233-242, July.
    18. Hsu, C.-H. & Wang, Fu-Kwun & Tzeng, Gwo-Hshiung, 2012. "The best vendor selection for conducting the recycled material based on a hybrid MCDM model combining DANP with VIKOR," Resources, Conservation & Recycling, Elsevier, vol. 66(C), pages 95-111.
    19. van der Rhee, Bo & Verma, Rohit & Plaschka, Gerhard, 2009. "Understanding trade-offs in the supplier selection process: The role of flexibility, delivery, and value-added services/support," International Journal of Production Economics, Elsevier, vol. 120(1), pages 30-41, July.
    20. Guertler, Benjamin & Spinler, Stefan, 2015. "When does operational risk cause supply chain enterprises to tip? A simulation of intra-organizational dynamics," Omega, Elsevier, vol. 57(PA), pages 54-69.

    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:29:y:2018:i:6:d:10.1007_s10845-015-1172-z. 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.