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国际原油现货市场价格剧烈波动,炼厂常用的采购策略不能应对由此产生的价格风险,该文针对这一问题提出了采购策略。以最小化总成本现值的期望为目标,根据原油采购的特点建立了动态规划模型,采用随机微积分方法分析了最优静态策略,并引入Bayes决策方法得到了动态策略。利用国际石油市场中某种基准原油近26年的历史价格数据,验证了模型的可行性和有效性。结果表明:基于Bayes方法的采购策略相比炼厂目前使用的策略能显著降低总成本,适用于原油采购问题。
International crude oil spot market price volatility, refinery commonly used procurement strategy can not cope with the resulting price risk, the paper proposed a procurement strategy for this issue. In order to minimize the present value of the total cost, a dynamic programming model is established according to the characteristics of crude oil procurement. The optimal static strategy is analyzed by stochastic calculus method, and the dynamic strategy is obtained by introducing Bayesian decision-making method. Using the historical price data of a certain benchmark oil in the international oil market for nearly 26 years, the feasibility and effectiveness of the model are verified. The results show that the procurement strategy based on Bayes method can significantly reduce the total cost compared with the current strategy of the refinery and is suitable for the purchase of crude oil.