Blending is an important unit operation in process industry. Blending scheduling is nonlinear optimiza- tion problem with constraints. It is difficult to obtain optimum solution by other general optimization methods. ...Blending is an important unit operation in process industry. Blending scheduling is nonlinear optimiza- tion problem with constraints. It is difficult to obtain optimum solution by other general optimization methods. Particle swarm optimization (PSO) algorithm is developed for nonlinear optimization problems with both contin- uous and discrete variables. In order to obtain a global optimum solution quickly, PSO algorithm is applied to solve the problem of blending scheduling under uncertainty. The calculation results based on an example of gasoline blending agree satisfactory with the ideal values, which illustrates that the PSO algorithm is valid and effective in solving the blending scheduling problem.展开更多
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 ...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.展开更多
For those refineries which have to deal with different types of crude oil, blending is an attractive solution to obtain a quality feedstock. In this paper, a novel scheduling strategy is proposed for a practical crude...For those refineries which have to deal with different types of crude oil, blending is an attractive solution to obtain a quality feedstock. In this paper, a novel scheduling strategy is proposed for a practical crude oil blending process. The objective is to keep the property of feedstock, mainly described by the true boiling point (TBP) data, consistent and suitable. Firstly, the mathematical model is established. Then, a heuristically initialized hybrid iterative (HIHI) algorithm based on a two-level optimization structure, in which tabu search (TS) and differential evolution (DE) are used for upper-level and lower-level optimization, respectively, is proposed to get the model solution. Finally, the effectiveness and efficiency of the scheduling strategy is validated via real data from a certain refinery.展开更多
In order to decrease the number of design variables and improve the efficiency of com- posite structure optimal design, a single-level composite structure optimization method based on a tapered model is presented. Com...In order to decrease the number of design variables and improve the efficiency of com- posite structure optimal design, a single-level composite structure optimization method based on a tapered model is presented. Compared with the conventional multi-level composite structure opti- mization method, this single-level method has many advantages. First, by using a distance variable and a ply group variable, the number of design variables is decreased evidently and independent with the density of sub-regions, which makes the single-level method very suitable for large-scale composite structures. Second, it is very convenient to optimize laminate thickness and stacking sequence in the same level, which probably improves the quality of optimal result. Third, ply con-tinuity can be guaranteed between sub-regions in the single-level method, which could reduce stress concentration and manufacturing difficulty. An example of a composite wing is used to demonstrate the advantages and competence of the single-level method proposed.展开更多
As we know, Newton's interpolation polynomial is based on divided differ-ences which can be calculated recursively by the divided-difference scheme while Thiele'sinterpolating continued fractions are geared to...As we know, Newton's interpolation polynomial is based on divided differ-ences which can be calculated recursively by the divided-difference scheme while Thiele'sinterpolating continued fractions are geared towards determining a rational functionwhich can also be calculated recursively by so-called inverse differences. In this paper,both Newton's interpolation polynomial and Thiele's interpolating continued fractionsare incorporated to yield a kind of bivariate vector valued blending rational interpolantsby means of the Samelson inverse. Blending differences are introduced to calculate theblending rational interpolants recursively, algorithm and matrix-valued case are dis-cussed and a numerical example is given to illustrate the efficiency of the algorithm.展开更多
Gasoline blending scheduling optimization can bring significant economic and efficient benefits to refineries.However,the optimization model is complex and difficult to build,which is a typical mixed integer nonlinear...Gasoline blending scheduling optimization can bring significant economic and efficient benefits to refineries.However,the optimization model is complex and difficult to build,which is a typical mixed integer nonlinear programming(MINLP)problem.Considering the large scale of the MINLP model,in order to improve the efficiency of the solution,the mixed integer linear programming-nonlinear programming(MILP-NLP)strategy is used to solve the problem.This paper uses the linear blending rules plus the blending effect correction to build the gasoline blending model,and a relaxed MILP model is constructed on this basis.The particle swarm optimization algorithm with niche technology(NPSO)is proposed to optimize the solution,and the high-precision soft-sensor method is used to calculate the deviation of gasoline attributes,the blending effect is dynamically corrected to ensure the accuracy of the blending effect and optimization results,thus forming a prediction-verification-reprediction closed-loop scheduling optimization strategy suitable for engineering applications.The optimization result of the MILP model provides a good initial point.By fixing the integer variables to the MILPoptimal value,the approximate MINLP optimal solution can be obtained through a NLP solution.The above solution strategy has been successfully applied to the actual gasoline production case of a refinery(3.5 million tons per year),and the results show that the strategy is effective and feasible.The optimization results based on the closed-loop scheduling optimization strategy have higher reliability.Compared with the standard particle swarm optimization algorithm,NPSO algorithm improves the optimization ability and efficiency to a certain extent,effectively reduces the blending cost while ensuring the convergence speed.展开更多
A new scheduling model for the bulk ore blending process in iron-making industry is presented,by converting the process into an assembly flow shop scheduling problem with sequence-depended setup time and limited inter...A new scheduling model for the bulk ore blending process in iron-making industry is presented,by converting the process into an assembly flow shop scheduling problem with sequence-depended setup time and limited intermediate buffer,and it facilitates the scheduling optimization for this process.To find out the optimal solution of the scheduling problem,an improved genetic algorithm hybridized with problem knowledge-based heuristics is also proposed,which provides high-quality initial solutions and fast searching speed.The efficiency of the algorithm is verified by the computational experiments.展开更多
With the development of computer vision technology,panoramic image stitching has been widely used in fields such as scene reconstruction.A single traditional image cannot fully capture the panoramic view of the iconic...With the development of computer vision technology,panoramic image stitching has been widely used in fields such as scene reconstruction.A single traditional image cannot fully capture the panoramic view of the iconic East Gate of the South Campus of Shaanxi University of Technology.Therefore,this project aims to technically fuse multiple partial images into a complete panoramic image,enabling comprehensive recording and visual presentation of the architectural landscapes and spatial environments in this area.This report first introduces the technical background and application scenarios,clarifying the necessity of panoramic image stitching in campus landscape recording.It then elaborates on the core objectives and practical values,highlighting the role of technical solutions in improving image quality.Technically,a modular system design based on OpenCV is adopted,including modules such as image preprocessing,feature extraction and matching,image registration,fusion,and post-processing.Specifically,the SIFT algorithm is applied for feature extraction,KNN combined with ratio testing is used for feature matching,image registration is achieved by calculating the homography matrix,the fusion process utilizes multiband blending and Laplacian pyramid,and post-processing includes operations such as black area filling and CLAHE contrast enhancement.The experiment was conducted in a specific hardware and software environment using five overlapping images.After preprocessing,stitching,detail enhancement,and black edge repair,a panoramic image was successfully generated.The results show that the panoramic image fully presents the relevant scenery,with concealed seams,balanced exposure differences,and strong hierarchical details.This report provides a systematic description of the project’s technical implementation and achievement application.展开更多
基金Supported by the National 863 Project (No. 2003AA412010) and the National 973 Program of China (No. 2002CB312201)
文摘Blending is an important unit operation in process industry. Blending scheduling is nonlinear optimiza- tion problem with constraints. It is difficult to obtain optimum solution by other general optimization methods. Particle swarm optimization (PSO) algorithm is developed for nonlinear optimization problems with both contin- uous and discrete variables. In order to obtain a global optimum solution quickly, PSO algorithm is applied to solve the problem of blending scheduling under uncertainty. The calculation results based on an example of gasoline blending agree satisfactory with the ideal values, which illustrates that the PSO algorithm is valid and effective in solving the blending scheduling problem.
基金supported by the National Natural Science Foundation of China(No.21365008)the Science Foundation of Guangxi province of China(No.2012GXNSFAA053230)
文摘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.
基金Supported by the National High Technology Research and Development Program of China （2007AA04Z193） the National Natural Science Foundation of China （60974008 60704032）
文摘For those refineries which have to deal with different types of crude oil, blending is an attractive solution to obtain a quality feedstock. In this paper, a novel scheduling strategy is proposed for a practical crude oil blending process. The objective is to keep the property of feedstock, mainly described by the true boiling point (TBP) data, consistent and suitable. Firstly, the mathematical model is established. Then, a heuristically initialized hybrid iterative (HIHI) algorithm based on a two-level optimization structure, in which tabu search (TS) and differential evolution (DE) are used for upper-level and lower-level optimization, respectively, is proposed to get the model solution. Finally, the effectiveness and efficiency of the scheduling strategy is validated via real data from a certain refinery.
基金supported by National Natural Science Foundation of China(No.1110216/A020312)Foundation Sciences of Northwestern Polytechnical University(No.JC20120210)
文摘In order to decrease the number of design variables and improve the efficiency of com- posite structure optimal design, a single-level composite structure optimization method based on a tapered model is presented. Compared with the conventional multi-level composite structure opti- mization method, this single-level method has many advantages. First, by using a distance variable and a ply group variable, the number of design variables is decreased evidently and independent with the density of sub-regions, which makes the single-level method very suitable for large-scale composite structures. Second, it is very convenient to optimize laminate thickness and stacking sequence in the same level, which probably improves the quality of optimal result. Third, ply con-tinuity can be guaranteed between sub-regions in the single-level method, which could reduce stress concentration and manufacturing difficulty. An example of a composite wing is used to demonstrate the advantages and competence of the single-level method proposed.
基金Supported by the National Natural Science Foundation of China under Grant No.10171026 and in part by the Foundation for Excellent Young Teachers of the Ministry of Education of China and the Financially-Aiding Program for the Backbone Teachers of the Min
文摘As we know, Newton's interpolation polynomial is based on divided differ-ences which can be calculated recursively by the divided-difference scheme while Thiele'sinterpolating continued fractions are geared towards determining a rational functionwhich can also be calculated recursively by so-called inverse differences. In this paper,both Newton's interpolation polynomial and Thiele's interpolating continued fractionsare incorporated to yield a kind of bivariate vector valued blending rational interpolantsby means of the Samelson inverse. Blending differences are introduced to calculate theblending rational interpolants recursively, algorithm and matrix-valued case are dis-cussed and a numerical example is given to illustrate the efficiency of the algorithm.
基金supported by National Natural Science Foundation of China(Basic Science Center Program:61988101)Shanghai Committee of Science and Technology(22DZ1101500)+1 种基金the National Natural Science Foundation of China(61973124,62073142)Fundamental Research Funds for the Central Universities。
文摘Gasoline blending scheduling optimization can bring significant economic and efficient benefits to refineries.However,the optimization model is complex and difficult to build,which is a typical mixed integer nonlinear programming(MINLP)problem.Considering the large scale of the MINLP model,in order to improve the efficiency of the solution,the mixed integer linear programming-nonlinear programming(MILP-NLP)strategy is used to solve the problem.This paper uses the linear blending rules plus the blending effect correction to build the gasoline blending model,and a relaxed MILP model is constructed on this basis.The particle swarm optimization algorithm with niche technology(NPSO)is proposed to optimize the solution,and the high-precision soft-sensor method is used to calculate the deviation of gasoline attributes,the blending effect is dynamically corrected to ensure the accuracy of the blending effect and optimization results,thus forming a prediction-verification-reprediction closed-loop scheduling optimization strategy suitable for engineering applications.The optimization result of the MILP model provides a good initial point.By fixing the integer variables to the MILPoptimal value,the approximate MINLP optimal solution can be obtained through a NLP solution.The above solution strategy has been successfully applied to the actual gasoline production case of a refinery(3.5 million tons per year),and the results show that the strategy is effective and feasible.The optimization results based on the closed-loop scheduling optimization strategy have higher reliability.Compared with the standard particle swarm optimization algorithm,NPSO algorithm improves the optimization ability and efficiency to a certain extent,effectively reduces the blending cost while ensuring the convergence speed.
基金Item Sponsored by National Key Technology Research and Development Program in 11th Five-Year Plan of China(2006AA04Z184)National Natural Science Foundation of China(60974023)
文摘A new scheduling model for the bulk ore blending process in iron-making industry is presented,by converting the process into an assembly flow shop scheduling problem with sequence-depended setup time and limited intermediate buffer,and it facilitates the scheduling optimization for this process.To find out the optimal solution of the scheduling problem,an improved genetic algorithm hybridized with problem knowledge-based heuristics is also proposed,which provides high-quality initial solutions and fast searching speed.The efficiency of the algorithm is verified by the computational experiments.
文摘With the development of computer vision technology,panoramic image stitching has been widely used in fields such as scene reconstruction.A single traditional image cannot fully capture the panoramic view of the iconic East Gate of the South Campus of Shaanxi University of Technology.Therefore,this project aims to technically fuse multiple partial images into a complete panoramic image,enabling comprehensive recording and visual presentation of the architectural landscapes and spatial environments in this area.This report first introduces the technical background and application scenarios,clarifying the necessity of panoramic image stitching in campus landscape recording.It then elaborates on the core objectives and practical values,highlighting the role of technical solutions in improving image quality.Technically,a modular system design based on OpenCV is adopted,including modules such as image preprocessing,feature extraction and matching,image registration,fusion,and post-processing.Specifically,the SIFT algorithm is applied for feature extraction,KNN combined with ratio testing is used for feature matching,image registration is achieved by calculating the homography matrix,the fusion process utilizes multiband blending and Laplacian pyramid,and post-processing includes operations such as black area filling and CLAHE contrast enhancement.The experiment was conducted in a specific hardware and software environment using five overlapping images.After preprocessing,stitching,detail enhancement,and black edge repair,a panoramic image was successfully generated.The results show that the panoramic image fully presents the relevant scenery,with concealed seams,balanced exposure differences,and strong hierarchical details.This report provides a systematic description of the project’s technical implementation and achievement application.
