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Modelling supply chain network for procurement of food grains in India

Mogale, D. G., Ghadge, Abhijeet, Krishna Kumar, Sri and Kumar Tiwari, Manoj 2019. Modelling supply chain network for procurement of food grains in India. International Journal of Production Research 10.1080/00207543.2019.1682707
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Abstract

The procurement of food grains from farmers and their transportation to regional level has become decisive due to increasing food demand and post-harvest losses in developing countries. To overcome these challenges, this paper attempts to develop a robust data-driven supply chain model for the efficient procurement of food grains in India. Following the data collected from three leading wheat producing Indian regions, a mixed-integer linear programming model is formulated for minimising total supply chain network costs and determining number and location of procurement centres. The NK Hybrid Genetic Algorithm (NKHGA) is employed to cluster the villages, along with a novel density-based approach to optimise the supply chain network. Sensitivity analysis indicates that policymakers should focus on creating an adequate number of procurement centres in each surplus state, well before the start of the harvesting season. The study is expected to benefit food grain supply chain stakeholders such as farmers, procurement agencies, logistics providers and government bodies in making an informed decision.

Item Type: Article
Date Type: Published Online
Status: Published
Schools: Business (Including Economics)
Publisher: Taylor & Francis
ISSN: 0020-7543
Date of First Compliant Deposit: 21 February 2020
Date of Acceptance: 8 October 2019
Last Modified: 17 Sep 2020 16:22
URI: http://orca.cf.ac.uk/id/eprint/129293

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