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Please use this identifier to cite or link to this item: http://bura.brunel.ac.uk/handle/2438/1055

Title: A decision model for natural oil buying policy under uncertainty
Authors: Poojari, CA
Lucas, CA
Mitra, G
Keywords: Natural oil cover policy; Stochastic program; Hedged decisions; Decision
Publication Date: 2004
Publisher: Brunel University
Abstract: A manufacturer, in a fast moving consumer goods industry, buys Natural oils from a number of oil suppliers world-wide. The prices of these oils are the major raw material cost in producing the consumer goods, which are also sold world-wide. The volatility in the international prices of the Natural oils has signi¯cant impact on the planning and budgets decisions. Since the oils are bought and the ¯nished products are sold in markets throughout the world, the manufacturer is exposed to a variety of market uncertainties and the resulting risks. These uncertainties are the raw material prices, the demand and the therefore the selling prices for the finished goods- all of which influence the profitability of the manufacturing firm. The risks can be minimised by entering into futures contract of appropriate duration, that is, by following a schedule of "forward"' purchase of oil (with specific series of future delivery dates) with the oil suppliers. We formulate this problem as a two-stage Stochastic Program (SP) using the futures and the spot prices for the Natural oil. This SP model gives robust decisions that hedge against the uncertainties in the Natural oil prices and the demand for the finished products. The uncertainty in the oil prices and the demand are modelled through a scenario generator. We have constructed a decision support system (DSS) that integrates the SP model, the scenario generator and the solution algorithm. This DSS also provides the decision maker a profile of the risk and return exposures for different policies.
URI: http://www.carisma.brunel.ac.uk/papers//CTR-27-04%20Chandra.pdf
http://bura.brunel.ac.uk/handle/2438/1055
Appears in Collections:Mathematics
School of Information Systems, Computing and Mathematics Research Papers

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