文章摘要
炼厂原油选购多目标优化
Multi-objective optimization of crude oil purchase in the refinery
投稿时间:2018-09-06  修订日期:2018-09-06
DOI:
中文关键词: 原油选购优化  混合整数非线性规划  多目标列队竞争算法
英文关键词: Crude oil purchase optimization  Mixed-integer nonlinear programming  Multi-objective line competition algorithm
基金项目:国家自然科学基金资助项目(21376185)
作者单位E-mail
王佩 武汉理工大学化学化工与生命科学学院 472265040@qq.com 
史彬 武汉理工大学化学化工与生命科学学院  
鄢烈祥 武汉理工大学化学化工与生命科学学院 hgxtgc@163.com 
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中文摘要:
      为保证原油加工装置的平稳生产和取得好的经济效益,大多数炼厂会同时选购几种原油进行混炼。原油选购优化现已成为提高炼厂效益的重要手段。以炼厂原油选购利润最大以及混合原油与目标原油的性质相对偏差最小作为目标,建立了一个多目标原油选购优化混合整数非线性规划模型。在多目标列队竞争算法(MOLCA)的基础上,改进了目标值的排序方式,并加入变异算子,提出了一种改进的多目标列队竞争算法(IMOLCA)。利用IMOLCA优化求解该模型,可以得到两优化目标的最优解集的Pareto 前沿。通过实例分析,验证了模型和算法的有效性。计算得到的方案可为炼厂原油选购提供参考。
英文摘要:
      In order to ensure the steady production and achieve economic benefits of crude oil processing unit, most refineries often need to control the blending properties and blend different types of crude oil simultaneously. Crude oil purchase optimization has become an important means to improve the economic benefits in refineries. The present work aims at maximizing the blending profit of crude oil purchase and minimizing the property relative deviation between blending crude oil and target crude oil. A multi-objective optimization of crude oil purchase model with mixed integer nonlinear programming is established. Based on the basic multi-objective line competition algorithm(MOLCA), we modified the sort means of target values and added mutation operator , an improved multi-objective line competition algorithm(IMOLCA) was proposed. Then the IMOLCA is employed to solve the optimization problem, which can obtain the Pareto frontier. By analysis of example based on IMOLCA, it is proved that the model and algorithm are effective. The blending solution can provide a reference for crude oil purchase in the refinery.
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