IDEAS home Printed from https://ideas.repec.org/a/taf/tprsxx/v57y2019i4p1214-1237.html
   My bibliography  Save this article

Multi-objective mixed integer programming and an application in a pharmaceutical supply chain

Author

Listed:
  • Sujeet Kumar Singh
  • Mark Goh

Abstract

Multi-objective integer linear and/or mixed integer linear programming (MOILP/MOMILP) are very useful for many areas of application as any model that incorporates discrete phenomena requires the consideration of integer variables. However, the research on the methods for the general multi-objective integer/mixed integer model has been scant when compared to multi-objective linear programming with continuous variables. In this paper, an MOMILP is proposed, which integrates various conflicting objectives. We give importance to the imprecise nature of some of the critical factors used in the modelling that can influence the effectiveness of the model. The uncertainty and the hesitation arising from estimating such imprecise parameters are represented by intuitionistic fuzzy numbers. The MOMILP model with intuitionistic fuzzy parameters is first converted into a crisp MOMILP model, using appropriate defuzzification strategies. Thereafter, the MOMILP is transformed into a single objective problem to yield a compromise solution with an acceptable degree of satisfaction, using suitable scalarisation techniques such as the gamma-connective technique and the minimum bounded sum operator technique. The proposed solution method is applied to several test problems and a multi-objective pharmaceutical supply chain management model with self generated random data.

Suggested Citation

  • Sujeet Kumar Singh & Mark Goh, 2019. "Multi-objective mixed integer programming and an application in a pharmaceutical supply chain," International Journal of Production Research, Taylor & Francis Journals, vol. 57(4), pages 1214-1237, February.
    • Handle: RePEc:taf:tprsxx:v:57:y:2019:i:4:p:1214-1237
    DOI: 10.1080/00207543.2018.1504172
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1080/00207543.2018.1504172
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1080/00207543.2018.1504172?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.

    Citations

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


    Cited by:

    1. Ronaldo Brito da Silva & Claudia Aparecida de Mattos, 2019. "Critical Success Factors of a Drug Traceability System for Creating Value in a Pharmaceutical Supply Chain (PSC)," IJERPH, MDPI, vol. 16(11), pages 1-18, June.
    2. Firoz Ahmad, 2022. "Interactive neutrosophic optimization technique for multiobjective programming problems: an application to pharmaceutical supply chain management," Annals of Operations Research, Springer, vol. 311(2), pages 551-585, April.
    3. Georgiou, Giorgos S. & Rouvas, Constantinos & Nathanael, Demetris, 2022. "Enhancing expansion of rooftop PV systems through Mixed Integer Linear Programming and Public Tender Procedures," Renewable Energy, Elsevier, vol. 187(C), pages 347-361.
    4. Fatemeh Shekoohi Tolgari & Naeme Zarrinpoor, 2024. "A robust reverse pharmaceutical supply chain design considering perishability and sustainable development objectives," Annals of Operations Research, Springer, vol. 340(2), pages 981-1033, September.
    5. Ieva Meidute-Kavaliauskiene & Figen Yıldırım & Shahryar Ghorbani & Renata Činčikaitė, 2022. "The Design of a Multi-Period and Multi-Echelon Perishable Goods Supply Network under Uncertainty," Sustainability, MDPI, vol. 14(4), pages 1-18, February.
    6. Ahmad, Firoz & Alnowibet, Khalid A. & Alrasheedi, Adel F. & Adhami, Ahmad Yusuf, 2022. "A multi-objective model for optimizing the socio-economic performance of a pharmaceutical supply chain," Socio-Economic Planning Sciences, Elsevier, vol. 79(C).
    7. Ieva Meidute-Kavaliauskiene & Halil Ibrahim Cebeci & Shahryar Ghorbani & Renata Činčikaitė, 2021. "An Integrated Approach for Evaluating Lean Innovation Practices in the Pharmaceutical Supply Chain," Logistics, MDPI, vol. 5(4), pages 1-17, October.

    More about this item

    Statistics

    Access and download statistics

    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:taf:tprsxx:v:57:y:2019:i:4:p:1214-1237. 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.

    We have no bibliographic references for this item. You can help adding them by using 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: Chris Longhurst (email available below). General contact details of provider: http://www.tandfonline.com/TPRS20 .

    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.