| 基于改进的布谷鸟搜索算法的原油选择与混合优化方法 |
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| 作者姓名： | Yang Huihua ;Ma Wei ;Zhang Xiaofeng ;Li Hu ;Tian Songbai |
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| 作者单位： | 1. 桂林电子科技大学;
2. 中国石化 石油化工科学研究院;
3. 中国石化石油化工科学研究院 |
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| 基金项目： | supported by the National Natural Science Foundation of China(No.21365008);the Science Foundation of Guangxi province of China(No.2012GXNSFAA053230) |
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| 摘 要： | Refineries often need to find similar crude oil to replace the scarce crude oil for stabilizing the feedstock property.We introduced the method for calculation of crude blended properties firstly, and then created a crude oil selection andblending optimization model based on the data of crude oil property. The model is a mixed-integer nonlinear programming（MINLP） with constraints, and the target is to maximize the similarity between the blended crude oil and the objective crudeoil. Furthermore, the model takes into account the selection of crude oils and their blending ratios simultaneously, and transformsthe problem of looking for similar crude oil into the crude oil selection and blending optimization problem. We appliedthe Improved Cuckoo Search （ICS） algorithm to solving the model. Through the simulations, ICS was compared withthe genetic algorithm, the particle swarm optimization algorithm and the CPLEX solver. The results show that ICS has verygood optimization efficiency. The blending solution can provide a reference for refineries to find the similar crude oil. Andthe method proposed can also give some references to selection and blending optimization of other materials.
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| 关 键 词： | crude oil similarity crude oil selection blending optimization mixed-integer nonlinear programming CuckooSearch algorithm |
A Method for Crude Oil Selection and Blending Optimization Based on Improved Cuckoo Search Algorithm |
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| Yang Huihua,;Ma Wei,;Zhang Xiaofeng,;Li Hu,;Tian Songbai.A Method for Crude Oil Selection and Blending Optimization Based on Improved Cuckoo Search Algorithm[J].China Petroleum Processing and Petrochemical Technology,2014,16(4):70-78. |
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| Authors: | Yang Huihua Ma Wei Zhang Xiaofeng Li Hu Tian Songbai |
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| Affiliation: | 1. Guangxi Experiment Center of Information Science, Guilin University of Electronic Technology, Guilin 541004
2. Research Institute of Petroleum Processing, SIN0PEC, Beijing 100083 |
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| Abstract: | Refineries often need to find similar crude oil to replace the scarce crude oil for stabilizing the feedstock property. We introduced the method for calculation of crude blended properties firstly, and then created a crude oil selection and blending optimization model based on the data of crude oil property. The model is a mixed-integer nonlinear programming(MINLP) with constraints, and the target is to maximize the similarity between the blended crude oil and the objective crude oil. Furthermore, the model takes into account the selection of crude oils and their blending ratios simultaneously, and transforms the problem of looking for similar crude oil into the crude oil selection and blending optimization problem. We applied the Improved Cuckoo Search(ICS) algorithm to solving the model. Through the simulations, ICS was compared with the genetic algorithm, the particle swarm optimization algorithm and the CPLEX solver. The results show that ICS has very good optimization efficiency. The blending solution can provide a reference for refineries to find the similar crude oil. And the method proposed can also give some references to selection and blending optimization of other materials. |
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| Keywords: | crude oil similarity crude oil selection blending optimization mixed-integer nonlinear programming Cuckoo Search algorithm |
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