IDEAS home Printed from https://ideas.repec.org/a/aii/ijcmss/v3y2012i2p67-71.html
   My bibliography  Save this article

Optimization of Supply Chain Efficiency in Multi Criteria Decision Environment Using AHP Model

Author

Listed:
  • N. Balaji

    (Research scholar, SRM School of Management, SRM University, Chennai, India)

  • Y. Lokeswara Choudary

    (Asst. Professor, SRM B-School, SRM University, Vadapalani, Chennai, India.)

Abstract

Inventory optimization is a key element in the global supply chain. Optimization can be achieved only through trail and error method from time to time in a dynamic environment. Inventory Optimization is can focus on the inventory positions based on customized requirements of the clients for independent products. It helps to gain a substantial market share by way of consistently satisfying the requirements of the clients.” Powerful optimization algorithms determine service levels and inventory targets for each product location leveraging demand forecast data, sales history, manufacturing and distribution assets, and transportation networks to consider the total landed cost of inventory – including transportation expenses, handling charges and holding costs – which can change dramatically and swiftly in today’s volatile environment. Time-phased execution accounts for demand trends and seasonality effects. Additionally, the solution also considers existing multi-environment network complexity, lead times, costs and constraints, as well as demand and supply variability. This Paper presents the different models with the empirical data to make decisions about supply chain organization using AHP model and highlights key factors to optimize the supply chains. The centralized organization model identifies process control , decentralized organization model indicates the need for time saving, centre led organization model and organization model fits with corporate strategy suggests the need for cost benefits, and finally, governance structure elevates the supply chain function emphasizes the need for time saving as primary factors for the optimization of supply chains in the market. The factors are identified through administration of AHP model on the real time data observed in the supply chain firm. Supply chain optimization is a regular function in a dynamic market and the success depends on the suitability of the model selected and degree of optimization administered in the supply chain function.

Suggested Citation

  • N. Balaji & Y. Lokeswara Choudary, 2012. "Optimization of Supply Chain Efficiency in Multi Criteria Decision Environment Using AHP Model," Indian Journal of Commerce and Management Studies, Educational Research Multimedia & Publications,India, vol. 3(2), pages 67-71, May.
  • Handle: RePEc:aii:ijcmss:v:3:y:2012:i:2:p:67-71
    as

    Download full text from publisher

    File URL: http://scholarshub.net/index.php/ijcms/article/view/329/320
    Download Restriction: no

    File URL: http://scholarshub.net/index.php/ijcms/article/view/329
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Alessio Ishizaka & Markus Lusti, 2006. "How to derive priorities in AHP: a comparative study," 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. 14(4), pages 387-400, December.
    2. Yoram Wind & Thomas L. Saaty, 1980. "Marketing Applications of the Analytic Hierarchy Process," Management Science, INFORMS, vol. 26(7), pages 641-658, 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. Jiří Mazurek & Konrad Kulakowski, 2020. "Information gap in value propositions of business models of language schools," Operations Research and Decisions, Wroclaw University of Science and Technology, Faculty of Management, vol. 30(2), pages 77-89.
    2. Corrente, Salvatore & Greco, Salvatore & Ishizaka, Alessio, 2016. "Combining analytical hierarchy process and Choquet integral within non-additive robust ordinal regression," Omega, Elsevier, vol. 61(C), pages 2-18.
    3. Jiří Mazurek, 2018. "Some notes on the properties of inconsistency indices in pairwise comparisons," Operations Research and Decisions, Wroclaw University of Science and Technology, Faculty of Management, vol. 28(1), pages 27-42.
    4. A Ishizaka & D Balkenborg & T Kaplan, 2011. "Influence of aggregation and measurement scale on ranking a compromise alternative in AHP," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 62(4), pages 700-710, April.
    5. C. Acuña-Soto & V. Liern & B. Pérez-Gladish, 2021. "Normalization in TOPSIS-based approaches with data of different nature: application to the ranking of mathematical videos," Annals of Operations Research, Springer, vol. 296(1), pages 541-569, January.
    6. Antonopoulos, I.-S. & Perkoulidis, G. & Logothetis, D. & Karkanias, C., 2014. "Ranking municipal solid waste treatment alternatives considering sustainability criteria using the analytical hierarchical process tool," Resources, Conservation & Recycling, Elsevier, vol. 86(C), pages 149-159.
    7. Pietro Amenta & Alessio Ishizaka & Antonio Lucadamo & Gabriella Marcarelli & Vijay Vyas, 2020. "Computing a common preference vector in a complex multi-actor and multi-group decision system in Analytic Hierarchy Process context," Annals of Operations Research, Springer, vol. 284(1), pages 33-62, January.
    8. Bice Cavallo, 2019. "Coherent weights for pairwise comparison matrices and a mixed-integer linear programming problem," Journal of Global Optimization, Springer, vol. 75(1), pages 143-161, September.
    9. Banai, Reza, 2010. "Evaluation of land use-transportation systems with the Analytic Network Process," The Journal of Transport and Land Use, Center for Transportation Studies, University of Minnesota, vol. 3(1), pages 85-112.
    10. Fatih Yiğit & Şakir Esnaf, 2021. "A new Fuzzy C-Means and AHP-based three-phased approach for multiple criteria ABC inventory classification," Journal of Intelligent Manufacturing, Springer, vol. 32(6), pages 1517-1528, August.
    11. Rachele Corticelli & Margherita Pazzini & Cecilia Mazzoli & Claudio Lantieri & Annarita Ferrante & Valeria Vignali, 2022. "Urban Regeneration and Soft Mobility: The Case Study of the Rimini Canal Port in Italy," Sustainability, MDPI, vol. 14(21), pages 1-27, November.
    12. Lin, Sheng-Hau & Zhao, Xiaofeng & Wu, Jiuxing & Liang, Fachao & Li, Jia-Hsuan & Lai, Ren-Ji & Hsieh, Jing-Chzi & Tzeng, Gwo-Hshiung, 2021. "An evaluation framework for developing green infrastructure by using a new hybrid multiple attribute decision-making model for promoting environmental sustainability," Socio-Economic Planning Sciences, Elsevier, vol. 75(C).
    13. Pishchulov, Grigory & Trautrims, Alexander & Chesney, Thomas & Gold, Stefan & Schwab, Leila, 2019. "The Voting Analytic Hierarchy Process revisited: A revised method with application to sustainable supplier selection," International Journal of Production Economics, Elsevier, vol. 211(C), pages 166-179.
    14. Seung-Jin Han & Won-Jae Lee & So-Hee Kim & Sang-Hoon Yoon & Hyunwoong Pyun, 2022. "Assessing Expected Long-term Benefits for the Olympic Games: Delphi-AHP Approach from Korean Olympic Experts," SAGE Open, , vol. 12(4), pages 21582440221, December.
    15. Denys Yemshanov & Frank H. Koch & Yakov Ben‐Haim & Marla Downing & Frank Sapio & Marty Siltanen, 2013. "A New Multicriteria Risk Mapping Approach Based on a Multiattribute Frontier Concept," Risk Analysis, John Wiley & Sons, vol. 33(9), pages 1694-1709, September.
    16. Ishizaka, Alessio & Siraj, Sajid & Nemery, Philippe, 2016. "Which energy mix for the UK (United Kingdom)? An evolutive descriptive mapping with the integrated GAIA (graphical analysis for interactive aid)–AHP (analytic hierarchy process) visualization tool," Energy, Elsevier, vol. 95(C), pages 602-611.
    17. Mangla, Sachin Kumar & Srivastava, Praveen Ranjan & Eachempati, Prajwal & Tiwari, Aviral Kumar, 2024. "Exploring the impact of key performance factors on energy markets: From energy risk management perspectives," Energy Economics, Elsevier, vol. 131(C).
    18. Seyed Rakhshan & Ali Kamyad & Sohrab Effati, 2015. "Ranking decision-making units by using combination of analytical hierarchical process method and Tchebycheff model in data envelopment analysis," Annals of Operations Research, Springer, vol. 226(1), pages 505-525, March.
    19. V. Srinivasan & G. Shainesh & Anand K. Sharma, 2015. "An approach to prioritize customer-based, cost-effective service enhancements," The Service Industries Journal, Taylor & Francis Journals, vol. 35(14), pages 747-762, October.
    20. Mónica García-Melón & Blanca Pérez-Gladish & Tomás Gómez-Navarro & Paz Mendez-Rodriguez, 2016. "Assessing mutual funds’ corporate social responsibility: a multistakeholder-AHP based methodology," Annals of Operations Research, Springer, vol. 244(2), pages 475-503, September.

    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:aii:ijcmss:v:3:y:2012:i:2:p:67-71. 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: Mr. Asif Anjum (email available below). General contact details of provider: .

    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.