炼油厂原油选购多目标优化

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王佩,史彬,鄢烈祥.炼油厂原油选购多目标优化[J].,2019,59(3):251-256

炼油厂原油选购多目标优化

Multi-objective optimization of crude oil purchase in refinery

DOI：10.7511/dllgxb201903005

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
王佩,史彬,鄢烈祥

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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，大多数炼油厂会通过控制混合性质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油厂经济效益的重要手段．以炼油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油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. Aiming at maximizing the profit of crude oil purchase and minimizing the property relative deviation between blending crude oil and target crude oil, a multi-objective optimization model of crude oil purchase with mixed integer nonlinear programming is established. Based on the basic multi-objective line competition algorithm (MOLCA), the sort means of target values is modified and mutation operator is added, and an improved multi-objective line competition algorithm (IMOLCA) is proposed. Then the IMOLCA is employed to solve the optimization model, which can obtain the Pareto frontier of two optimization target solution sets. By analysis of example, 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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炼油厂原油选购多目标优化

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