Please use this identifier to cite or link to this item: http://repository.kln.ac.lk/handle/123456789/19039
Title: An optimization model for planning milling quantities based on forecasting of paddy and rice prices
Authors: Abeyweera, S.
Nanayakkara, J.
Keywords: Milling capacity optimization
Linear programming
Operation research
Sri Lankan agricultural industry
Rice supply chain
Issue Date: 2018
Publisher: International Research Conference on Smart Computing and Systems Engineering - SCSE 2018
Citation: Abeyweera,S. and Nanayakkara,J. (2018). An optimization model for planning milling quantities based on forecasting of paddy and rice prices. International Research Conference on Smart Computing and Systems Engineering - SCSE 2018, Department of Industrial Management, Faculty of Science, University of Kelaniya, Sri Lanka. p.217.
Abstract: Rice is considered as the staple food of Sri Lanka. The conversion of paddy in to rice is a main value creation found in the Sri Lankan agricultural industries. The paper deals with the planning concerns, in the supply chain of rice. The paper discusses various issues related to production of rice at the downstream end of the supply chain and milling management decisions. Small and Medium scale milling plants around Sri Lanka are facing problems of dissolving their businesses quickly, and they are in a need to utilize their capacity in optimal way. An efficient supply chain management framework is essential for the milling to be efficient in sourcing, processing and distribution of rice under an uncertain environment. In the study, the behaviour of the Sri Lankan paddy and rice market prices volatility has been studied qualitatively and the paper discusses the validity of applying different forecasting tools. Mainly the SARIMA and Winters model have been used for forecasting. The study identifies and proposes two price regions for forecasting, based on the macro environmental factors. In order to attain the research objectives of optimization, the researcher has used linear programming as a continuous multi period model. The research is significant for the small and medium scale milling community to enhance their livelihood by determining the right time and right quantity for procuring, processing and stocking in a volatile market environment.
URI: http://repository.kln.ac.lk/handle/123456789/19039
Appears in Collections:Smart Computing and Systems Engineering - 2018 (SCSE 2018)

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