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An Optimal Jatropha Seed Warehouse Location Decision Using Myopic and Exchange Heuristics of P Median

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Proceedings of 2012 3rd International Asia Conference on Industrial Engineering and Management Innovation (IEMI2012)

Abstract

India has a vast cultivable land and almost all seasons for production of all varieties of fruits and vegetables. However, India has also got a wide uncultivable waste lands. Jatropha seed is one of the highly suitable agricultural product for making an alternate fuel. As this seed can grow in any type of land it is necessary to focus on producing an alternate fuel with help of esterification process. Nearly 90% of the country’s food and vegetable produce is handled by private organizations only. The goods cross at least five stages before reaching to the end customers. This leads to the hike in prices of the goods

The Jatropha oil production process involves many stages of supply chain. In this paper an identification of optimal collection center for Jatropha seed which serves as the common point for the farmers (Producers) is focussed. This collection center facility may change significantly as per the policy of the government. The costs, production capacity, travel distance, mode of transport, time and other input variables of facility location models are highly uncertain. The p median algorithm is used to identify the optimal collection centers. Also it captures the various operational functions of the Jatropha supply chain uncertainty including distance, demand, graphical location etc., as the people have more flexibility to choose the collection center location, the facilities need to be modified in terms of farmers constraints. This paper assesses the field data and identified the optimal solution using Myopic and Exchange heuristics algorithms

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Correspondence to S. P. Srinivasan .

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Srinivasan, S.P., Malliga, P. (2013). An Optimal Jatropha Seed Warehouse Location Decision Using Myopic and Exchange Heuristics of P Median. In: Dou, R. (eds) Proceedings of 2012 3rd International Asia Conference on Industrial Engineering and Management Innovation (IEMI2012). Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-33012-4_44

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