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Plant location selection of a manufacturing industry using analytic hierarchy process approach

Author

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  • Suman Gothwal
  • Rajeev Saha

Abstract

Selection of plant location is a multi-person and multi-criteria decision problem. Location selection is a strategic decision that cannot be changed overnight. Even if the location decision is changed at all, a considerable loss is bound to be incurred. Without sound location planning in the beginning, the new facility may pose continuous operating disadvantages for the future operations. In this paper, analytic hierarchy process (AHP) approach is used to arrive at consensus decision. The AHP model is formulated and applied to a real case study to examine its feasibility in selecting the plant location for a manufacturing industry. Different factors were identified affecting the plant location on the five locations (Delhi, Manesar, Chandigarh, Mumbai and Baddi) suggested by a particular manufacturing industry and then AHP technique was implemented to select the best location out of these five locations. After analysis, Baddi is found to be the best location to setup their new plant. AHP is a powerful and flexible tool for tackling the complex decision problem into a simple concept of hierarchy, which incorporates both financial and non-financial factors influencing the decision alternatives in a systematic way.

Suggested Citation

  • Suman Gothwal & Rajeev Saha, 2015. "Plant location selection of a manufacturing industry using analytic hierarchy process approach," International Journal of Services and Operations Management, Inderscience Enterprises Ltd, vol. 22(2), pages 235-255.
    • Handle: RePEc:ids:ijsoma:v:22:y:2015:i:2:p:235-255
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    Citations

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    Cited by:

    1. Vijay Pereira & Umesh Bamel, 2023. "Charting the managerial and theoretical evolutionary path of AHP using thematic and systematic review: a decadal (2012–2021) study," Annals of Operations Research, Springer, vol. 326(2), pages 635-651, July.
    2. Pasura Aungkulanon & Walailak Atthirawong & Woranat Sangmanee & Pongchanun Luangpaiboon, 2023. "Fuzzy Techniques and Adjusted Mixture Design-Based Scenario Analysis in the CLMV (Cambodia, Lao PDR, Myanmar and Vietnam) Subregion for Multi-Criteria Decision Making in the Apparel Industry," Mathematics, MDPI, vol. 11(23), pages 1-32, November.
    3. Konstantinos G. Aravossis & Vasilis C. Kapsalis & Grigorios L. Kyriakopoulos & Theofanis G. Xouleis, 2019. "Development of a Holistic Assessment Framework for Industrial Organizations," Sustainability, MDPI, vol. 11(14), pages 1-24, July.
    4. Andrés Fernández-Miguel & Maria Pia Riccardi & Valerio Veglio & Fernando E. García-Muiña & Alfonso P. Fernández del Hoyo & Davide Settembre-Blundo, 2022. "Disruption in Resource-Intensive Supply Chains: Reshoring and Nearshoring as Strategies to Enable Them to Become More Resilient and Sustainable," Sustainability, MDPI, vol. 14(17), pages 1-13, August.
    5. López, Cristina & Ishizaka, Alessio, 2019. "A hybrid FCM-AHP approach to predict impacts of offshore outsourcing location decisions on supply chain resilience," Journal of Business Research, Elsevier, vol. 103(C), pages 495-507.

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