IDEAS home Printed from https://ideas.repec.org/a/eee/ejores/v209y2011i3p253-264.html
   My bibliography  Save this article

Possibilistic linear-programming approach for supply chain networking decisions

Author

Listed:
  • Kabak, Özgür
  • Ülengin, Füsun

Abstract

Supply chain networking decisions are very important for the medium- and long-term planning success of manufacturing companies. The inputs to supply chain planning models are subject to environmental and system uncertainties. In this paper, a fuzzy set theory-based model is proposed to deal with those uncertainties. For this purpose, a possibilistic linear programming (PLP) model is used to make strategic resource-planning decisions using fuzzy demand forecasts and fuzzy yield rates as well as other inputs such as costs and capacities. The objective of the proposed PLP is to maximize the total profit of the enterprise. The model is applied to Mercedes-Benz Türk, one of the largest bus-manufacturing companies in the world, and conclusions and suggestions for further research are provided.

Suggested Citation

  • Kabak, Özgür & Ülengin, Füsun, 2011. "Possibilistic linear-programming approach for supply chain networking decisions," European Journal of Operational Research, Elsevier, vol. 209(3), pages 253-264, March.
    • Handle: RePEc:eee:ejores:v:209:y:2011:i:3:p:253-264
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0377-2217(10)00623-5
    Download Restriction: Full text for ScienceDirect subscribers only
    ---><---

    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. Lakhal, Salem Y., 2006. "An operational profit sharing and transfer pricing model for network-manufacturing companies," European Journal of Operational Research, Elsevier, vol. 175(1), pages 543-565, November.
    2. Maity, K. & Maiti, M., 2007. "Possibility and necessity constraints and their defuzzification--A multi-item production-inventory scenario via optimal control theory," European Journal of Operational Research, Elsevier, vol. 177(2), pages 882-896, March.
    3. Petrovic, Dobrila, 2001. "Simulation of supply chain behaviour and performance in an uncertain environment," International Journal of Production Economics, Elsevier, vol. 71(1-3), pages 429-438, May.
    4. Stanciulescu, C. & Fortemps, Ph. & Installe, M. & Wertz, V., 2003. "Multiobjective fuzzy linear programming problems with fuzzy decision variables," European Journal of Operational Research, Elsevier, vol. 149(3), pages 654-675, September.
    5. Das, Sanchoy K. & Abdel-Malek, Layek, 2003. "Modeling the flexibility of order quantities and lead-times in supply chains," International Journal of Production Economics, Elsevier, vol. 85(2), pages 171-181, August.
    6. Petrovic, Dobrila & Roy, Rajat & Petrovic, Radivoj, 1999. "Supply chain modelling using fuzzy sets," International Journal of Production Economics, Elsevier, vol. 59(1-3), pages 443-453, March.
    7. Sabri, Ehap H. & Beamon, Benita M., 2000. "A multi-objective approach to simultaneous strategic and operational planning in supply chain design," Omega, Elsevier, vol. 28(5), pages 581-598, October.
    8. Lakhal, Salem & Martel, Alain & Kettani, Ossama & Oral, Muhittin, 2001. "On the optimization of supply chain networking decisions," European Journal of Operational Research, Elsevier, vol. 129(2), pages 259-270, March.
    9. Wang, Juite & Shu, Yun-Feng, 2007. "A possibilistic decision model for new product supply chain design," European Journal of Operational Research, Elsevier, vol. 177(2), pages 1044-1061, March.
    10. Schneeweiss, Christoph, 2003. "Distributed decision making--a unified approach," European Journal of Operational Research, Elsevier, vol. 150(2), pages 237-252, October.
    11. Wang, Reay-Chen & Fang, Hsiao-Hua, 2001. "Aggregate production planning with multiple objectives in a fuzzy environment," European Journal of Operational Research, Elsevier, vol. 133(3), pages 521-536, September.
    12. Wang, Reay-Chen & Liang, Tien-Fu, 2005. "Applying possibilistic linear programming to aggregate production planning," International Journal of Production Economics, Elsevier, vol. 98(3), pages 328-341, December.
    13. Gunasekaran, Angappa & Lai, Kee-hung & Edwin Cheng, T.C., 2008. "Responsive supply chain: A competitive strategy in a networked economy," Omega, Elsevier, vol. 36(4), pages 549-564, August.
    14. Pramanik, Surapati & Roy, Tapan Kumar, 2007. "Fuzzy goal programming approach to multilevel programming problems," European Journal of Operational Research, Elsevier, vol. 176(2), pages 1151-1166, January.
    15. Fandel, G. & Stammen, M., 2004. "A general model for extended strategic supply chain management with emphasis on product life cycles including development and recycling," International Journal of Production Economics, Elsevier, vol. 89(3), pages 293-308, June.
    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. Huang, Edward & Goetschalckx, Marc, 2014. "Strategic robust supply chain design based on the Pareto-optimal tradeoff between efficiency and risk," European Journal of Operational Research, Elsevier, vol. 237(2), pages 508-518.
    2. Wenhao Kang & Chi Fai Cheung, 2023. "Banking System Incidents Analysis Using Knowledge Graph," International Journal of Knowledge and Systems Science (IJKSS), IGI Global, vol. 14(1), pages 1-23, January.
    3. Maharjan, Rajali & Hanaoka, Shinya, 2020. "A credibility-based multi-objective temporary logistics hub location-allocation model for relief supply and distribution under uncertainty," Socio-Economic Planning Sciences, Elsevier, vol. 70(C).
    4. Aniruddh Nain & Deepika Jain & Shivam Gupta & Ashwani Kumar, 2023. "Improving First Responders' Effectiveness in Post-Disaster Scenarios Through a Hybrid Framework for Damage Assessment and Prioritization," Global Journal of Flexible Systems Management, Springer;Global Institute of Flexible Systems Management, vol. 24(3), pages 409-437, September.
    5. Volling, Thomas & Matzke, Andreas & Grunewald, Martin & Spengler, Thomas S., 2013. "Planning of capacities and orders in build-to-order automobile production: A review," European Journal of Operational Research, Elsevier, vol. 224(2), pages 240-260.
    6. Angus Jeang, 2019. "Robust DEA methodology via computer model for conceptual design under uncertainty," Journal of Intelligent Manufacturing, Springer, vol. 30(3), pages 1221-1245, March.
    7. Tofighi, S. & Torabi, S.A. & Mansouri, S.A., 2016. "Humanitarian logistics network design under mixed uncertainty," European Journal of Operational Research, Elsevier, vol. 250(1), pages 239-250.
    8. Ali Torabi, S. & Shokr, Iman & Tofighi, Saeideh & Heydari, Jafar, 2018. "Integrated relief pre-positioning and procurement planning in humanitarian supply chains," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 113(C), pages 123-146.

    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. Shih-Pin Chen, 2017. "Effects of fuzzy data on decision making in a competitive supply chain," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 68(10), pages 1146-1160, October.
    2. Tang, Christopher S. & Davarzani, Hoda & Sarkis, Joseph, 2015. "Quantitative models for managing supply chain risks: A reviewAuthor-Name: Fahimnia, Behnam," European Journal of Operational Research, Elsevier, vol. 247(1), pages 1-15.
    3. 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.
    4. Peidro, David & Mula, Josefa & Jiménez, Mariano & del Mar Botella, Ma, 2010. "A fuzzy linear programming based approach for tactical supply chain planning in an uncertainty environment," European Journal of Operational Research, Elsevier, vol. 205(1), pages 65-80, August.
    5. Das, Kanchan, 2011. "Integrating effective flexibility measures into a strategic supply chain planning model," European Journal of Operational Research, Elsevier, vol. 211(1), pages 170-183, May.
    6. Farahani, Reza Zanjirani & Rezapour, Shabnam & Drezner, Tammy & Fallah, Samira, 2014. "Competitive supply chain network design: An overview of classifications, models, solution techniques and applications," Omega, Elsevier, vol. 45(C), pages 92-118.
    7. Tachizawa, Elcio M. & Gimenez, Cristina, 2010. "Supply flexibility strategies in Spanish firms: Results from a survey," International Journal of Production Economics, Elsevier, vol. 124(1), pages 214-224, March.
    8. Vahdani, Behnam & Mohammadi, M., 2015. "A bi-objective interval-stochastic robust optimization model for designing closed loop supply chain network with multi-priority queuing system," International Journal of Production Economics, Elsevier, vol. 170(PA), pages 67-87.
    9. Yasser A. Davizón & César Martínez-Olvera & Rogelio Soto & Carlos Hinojosa & Piero Espino-Román, 2015. "Optimal Control Approaches to the Aggregate Production Planning Problem," Sustainability, MDPI, vol. 7(12), pages 1-16, December.
    10. Shih-Pin Chen & Wen-Lung Huang, 2014. "Solving Fuzzy Multiproduct Aggregate Production Planning Problems Based on Extension Principle," International Journal of Mathematics and Mathematical Sciences, Hindawi, vol. 2014, pages 1-18, August.
    11. Renato Matta, 2019. "Product costing in the strategic formation of a supply chain," Annals of Operations Research, Springer, vol. 272(1), pages 389-427, January.
    12. Wang, Juite & Shu, Yun-Feng, 2007. "A possibilistic decision model for new product supply chain design," European Journal of Operational Research, Elsevier, vol. 177(2), pages 1044-1061, March.
    13. Moncayo-Martínez, Luis A. & Zhang, David Z., 2013. "Optimising safety stock placement and lead time in an assembly supply chain using bi-objective MAX–MIN ant system," International Journal of Production Economics, Elsevier, vol. 145(1), pages 18-28.
    14. Roozbeh Nia, Ali & Hemmati Far, Mohammad & Akhavan Niaki, Seyed Taghi, 2014. "A fuzzy vendor managed inventory of multi-item economic order quantity model under shortage: An ant colony optimization algorithm," International Journal of Production Economics, Elsevier, vol. 155(C), pages 259-271.
    15. Turan Paksoy & Eren Özceylan & Gerhard-Wilhelm Weber, 2013. "Profit oriented supply chain network optimization," 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. 21(2), pages 455-478, March.
    16. Wang, Chao & Lim, Ming K & Zhao, Longfeng & Tseng, Ming-Lang & Chien, Chen-Fu & Lev, Benjamin, 2020. "The evolution of Omega-The International Journal of Management Science over the past 40 years: A bibliometric overview," Omega, Elsevier, vol. 93(C).
    17. Vila, Didier & Martel, Alain & Beauregard, Robert, 2006. "Designing logistics networks in divergent process industries: A methodology and its application to the lumber industry," International Journal of Production Economics, Elsevier, vol. 102(2), pages 358-378, August.
    18. F. Jolai & J. Razmi & N. Rostami, 2011. "A fuzzy goal programming and meta heuristic algorithms for solving integrated production: distribution planning problem," 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. 19(4), pages 547-569, December.
    19. Zhaobo Chen & Chunxian Teng & Ding Zhang & Jiayi Sun, 2016. "Modelling inter-supply chain competition with resource limitation and demand disruption," International Journal of Systems Science, Taylor & Francis Journals, vol. 47(7), pages 1644-1658, May.
    20. Perron, Sylvain & Hansen, Pierre & Le Digabel, Sébastien & Mladenovic, Nenad, 2010. "Exact and heuristic solutions of the global supply chain problem with transfer pricing," European Journal of Operational Research, Elsevier, vol. 202(3), pages 864-879, May.

    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:eee:ejores:v:209:y:2011:i:3:p:253-264. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/eor .

    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.