Taking the ratio of heat transfer area to net power and heat recovery efficiency into account, a multi-objective mathematical model was developed for organic Rankine cycle （ORC）. Working fluids considered were R123,...Taking the ratio of heat transfer area to net power and heat recovery efficiency into account, a multi-objective mathematical model was developed for organic Rankine cycle （ORC）. Working fluids considered were R123, R134a, R141b, R227ea and R245fa. Under the given conditions, the parameters including evaporating and condensing pressures, working fluid and cooling water velocities were optimized by simulated annealing algorithm. The results show that the optimal evaporating pressure increases with the heat source temperature increasing. Compared with other working fluids, R123 is the best choice for the temperature range of 100--180℃ and R141 b shows better performance when the temperature is higher than 180 ℃. Economic characteristic of system decreases rapidly with the decrease of heat source temperature. ORC system is uneconomical for the heat source temperature lower than 100℃.展开更多
Multivariate statistical process monitoring methods are often used in chemical process fault diagnosis.In this article,(I)the cycle temporal algorithm(CTA)combined with the dynamic kernel principal component analysis(...Multivariate statistical process monitoring methods are often used in chemical process fault diagnosis.In this article,(I)the cycle temporal algorithm(CTA)combined with the dynamic kernel principal component analysis(DKPCA)and the multiway dynamic kernel principal component analysis(MDKPCA)fault detection algorithms are proposed,which are used for continuous and batch process fault detections,respectively.In addition,(II)a fault variable identification model based on reconstructed-based contribution(RBC)model that paves the way for determining the cause of the fault are proposed.The proposed fault diagnosis model was applied to Tennessee Eastman(TE)process and penicillin fermentation process for fault diagnosis.And compare with other fault diagnosis methods.The results show that the proposed method has better detection effects than other methods.Finally,the reconstruction-based contribution(RBC)model method is used to accurately locate the root cause of the fault and determine the fault path.展开更多
This paper proposes a low complexity control scheme for voltage control of a dynamic voltage restorer(DVR)in a three-phase system.The control scheme employs the fractional order,proportional-integral-derivative(FOPID)...This paper proposes a low complexity control scheme for voltage control of a dynamic voltage restorer(DVR)in a three-phase system.The control scheme employs the fractional order,proportional-integral-derivative(FOPID)controller to improve on the DVR performance in order to enhance the power quality in terms of the response time,steady-state error and total harmonic distortion(THD).The result obtained was compared with fractional order,proportionalintegral(FOPI),proportional-integral-derivative(PID)and proportional-integral(PI)controllers in order to show the effectiveness of the proposed DVR control scheme.A water cycle optimization algorithm(WCA)was utilized to find the optimal set for all the controller gains.They were used to solve four power quality issues;balanced voltage sag,balanced voltage swell,unbalanced voltage sag,and unbalanced voltage swell.It showed that one set of controller gain obtained from the WCA could solve all the power quality issues while the others in the literature needed an individual set of optimal gain for each power quality problem.To prove the concept,the proposed DVR algorithm was simulated in the MATLAB/Simulink software and the results revealed that the four optimal controllers can compensate for all the power quality problems.A comparative analysis of the results in various aspects of their dynamic response and%THD was discussed and analyzed.It was found that PID controller yields the most rapid performance in terms of average response time while FOPID controller yields the best performance in term of average%steady-state error.FOPI controller was found to provide the lowest THD percentage in the average%THD.FOPID did not differ much in average response from the PID and average%THD from FOPI;however,FOPID provided the most outstanding average steady-state error.According to the CBMA curve,the dynamic responses of all controllers fall in the acceptable power quality area.The total harmonic distortion(THD)of the compensated load voltage from all the controllers were within the 8%limit in accordance to the IEEE std.519-2014.展开更多
Wind farm layout optimization is a critical challenge in renewable energy development,especially in regions with complex terrain.Micro-siting of wind turbines has a significant impact on the overall efficiency and eco...Wind farm layout optimization is a critical challenge in renewable energy development,especially in regions with complex terrain.Micro-siting of wind turbines has a significant impact on the overall efficiency and economic viability of wind farm,where the wake effect,wind speed,types of wind turbines,etc.,have an impact on the output power of the wind farm.To solve the optimization problem of wind farm layout under complex terrain conditions,this paper proposes wind turbine layout optimization using different types of wind turbines,the aim is to reduce the influence of the wake effect and maximize economic benefits.The linear wake model is used for wake flow calculation over complex terrain.Minimizing the unit energy cost is taken as the objective function,considering that the objective function is affected by cost and output power,which influence each other.The cost function includes construction cost,installation cost,maintenance cost,etc.Therefore,a bi-level constrained optimization model is established,in which the upper-level objective function is to minimize the unit energy cost,and the lower-level objective function is to maximize the output power.Then,a hybrid evolutionary algorithm is designed according to the characteristics of the decision variables.The improved genetic algorithm and differential evolution are used to optimize the upper-level and lower-level objective functions,respectively,these evolutionary operations search for the optimal solution as much as possible.Finally,taking the roughness of different terrain,wind farms of different scales and different types of wind turbines as research scenarios,the optimal deployment is solved by using the algorithm in this paper,and four algorithms are compared to verify the effectiveness of the proposed algorithm.展开更多
An effective Luby transform （LT） encoding algorithm based on short cycle elimination is proposed to improve decoding probabilities of short length LT codes. By searching the generator ma- trix, some special encoded ...An effective Luby transform （LT） encoding algorithm based on short cycle elimination is proposed to improve decoding probabilities of short length LT codes. By searching the generator ma- trix, some special encoded symbols are generated by the encoder to effectively break the short cycles that have negative effect on the performance of LT codes. Analysis and numerical results show that by employing the proposed algorithm, the encoding complexity decreases and the decoding probabili- ties improve both in binary erasure channels （BECs） and additive white gauss noise （AWGN） chan- nels.展开更多
We put forward an alternative quantum algorithm for finding ttamiltonian cycles in any N-vertex graph based on adiabatic quantum computing. With a yon Neumann measurement on the final state, one may determine whether ...We put forward an alternative quantum algorithm for finding ttamiltonian cycles in any N-vertex graph based on adiabatic quantum computing. With a yon Neumann measurement on the final state, one may determine whether there is a HamiRonian cycle in the graph and pick out a cycle if there is any. Although the proposed algorithm provides a quadratic speedup, it gives an alternative algorithm based on adiabatic quantum computation, which is of interest because of its inherent robustness.展开更多
铁路光传送网络是高速铁路地面基础设施的神经中枢,为避免网络故障给铁路运营带来巨大损失,重点研究光传送网P-Cycle(Pre-configured Cycle)保护技术,提出在圈扩展时以所有候选圈上未保护工作容量的方差、冗余度两个指标为比较标准的RVP...铁路光传送网络是高速铁路地面基础设施的神经中枢,为避免网络故障给铁路运营带来巨大损失,重点研究光传送网P-Cycle(Pre-configured Cycle)保护技术,提出在圈扩展时以所有候选圈上未保护工作容量的方差、冗余度两个指标为比较标准的RVPA(Redundancy and Variance Based P-Cycle Construction Algorithm)算法。圈扩展的过程中,算法将选择方差与冗余度能同时满足条件的候选圈作为本轮扩展圈,有效限制了完成保护的P-Cycle圈个数;圈扩展停止条件中,当UPL与参数M、冗余度的大小关系满足条件时,则停止圈扩展,从而限制圈上节点数,使圈个数与圈长度得到有效均衡;在仿真过程中,利用泛欧网络拓扑COST239对RVPA算法进行仿真,并对比分析不同M值下的性能。仿真结果表明,在相同空闲资源与待保护工作容量设定下,参数M取0.5时效果最优,并且RVPA算法的保护容量效率、所需圈的个数、算法整体耗时、总冗余度均优于已有的POCA(P-Cycle Optimization Configuration Heuristic Algorithm)算法。展开更多
Due to the fact that headway is a key factor to be considered in bus scheduling, this paper proposes a bi-level programming model for optimizing bus headway in public transit lines. In this model, with the interests o...Due to the fact that headway is a key factor to be considered in bus scheduling, this paper proposes a bi-level programming model for optimizing bus headway in public transit lines. In this model, with the interests of bus companies and passengers in mind, the upper-level model＇s objective is to minimize the total cost, which is affected by frequency settings, both in time and economy in the transit system. The lower-level model is a transit assignment model used to describe the assignment of passengers＇ trips to the network based on the optimal bus headway. In order to solve the proposed model, a hybrid genetic algorithm, namely the genetic algorithm and the simulated annealing algorithm （GA-SA）, is designed. Finally, the model and the algorithm are tested against the transit data, by taking some of the bus lines of Changzhou city as an example. Results indicate that the proposed model allows supply and demand to be linked, which is reasonable, and the solving algorithm is effective.展开更多
Based on genetic algorithms, a solution algorithm is presented for the bi-level decision making problem with continuous variables in the upper level in accordance with the bi-level decision making principle. The algor...Based on genetic algorithms, a solution algorithm is presented for the bi-level decision making problem with continuous variables in the upper level in accordance with the bi-level decision making principle. The algorithm is compared with Monte Carlo simulated annealing algorithm, and its feasibility and effectiveness are verified with two calculating examples.展开更多
A genetic-fuzzy HEV control strategy based on driving cycle recognition （DCR） was built. Six driving cycles were selected to represent different traffic conditions e.g. freeway, urban, suburb. A neural algorithm was...A genetic-fuzzy HEV control strategy based on driving cycle recognition （DCR） was built. Six driving cycles were selected to represent different traffic conditions e.g. freeway, urban, suburb. A neural algorithm was used for traffic condition recognition based on ten parameters of each driving cycle. The DCR was utilized for optimization of the HEV control parameters using a genetic-fuzzy approach. A fuzzy logic controller （FLC） was designed to be intelligent to manage the engine to work in the vicinity of its optimal condition. The fuzzy membership function parameters were optimized using the genetic algorithm （GA） for each driving cycle. The result is that the DCR_ fuzzy controller can reduce the fuel consumption by 1. 9%, higher than only CYC _ HWFET optimized fuzzy （0.2%） or CYC _ WVUSUB optimized fuzzy （0.7%）. The DCR_ fuzzy method can get the better result than only optimizing one cycle on the complex real traffic conditions.展开更多
In reference to the method of the Conference Board,the coincident indexes for China are constructed from a sample period between January 1990 and May 2012 and by51 chosen component indicators.The resulting coincident ...In reference to the method of the Conference Board,the coincident indexes for China are constructed from a sample period between January 1990 and May 2012 and by51 chosen component indicators.The resulting coincident indexes have higher correlations with gross domestic product(GDP) growth rates than the China Economic Monitoring and Analysis Center(CEMAC) coincident index over the sample period between February2005 and May 2012.The peaks and troughs of the growth rates in several indicators are identified.The total number of peaks and troughs in the resulting coincident index is the same with the CEMAC coincident index.Unfortunately,these troughs don't signify recessions in the Chinese economy because the financial system has not seen a negative growth rate over the specific sample periods.The impacts of the Southeast Asian Financial Crisis and subprime mortgage crisis on the business cycle could be dated via a smoother index from HP filtering to the coincident index.展开更多
In silico approaches for metabolites optimization have been derived from the flood of sequenced and annotated genomes. However, there exist still numerous degrees of freedom in terms of optimization algorithm approach...In silico approaches for metabolites optimization have been derived from the flood of sequenced and annotated genomes. However, there exist still numerous degrees of freedom in terms of optimization algorithm approaches that can be exploited in order to enhance yield of processes which are based on biological reactions. Here, we propose an evolutionary approach aiming to suggest different mutant for augmenting ethanol yield using glycerol as substrate in Escherichia coli. We found that this algorithm, even though is far from providing the global optimum, is able to uncover genes that a global optimizer would be incapable of. By over-expressing accB, eno, dapE, and accA mutants in ethanol production was augmented up to 2 fold compared to its counterpart E. coli BW25113.展开更多
The research on scheduling and heat integration of batch process plays an important role in reducing energy consumption,improving production efficiency and enhancing the competitiveness of industries.The complexity an...The research on scheduling and heat integration of batch process plays an important role in reducing energy consumption,improving production efficiency and enhancing the competitiveness of industries.The complexity and difficulty of the model solving are increased due to the comprehensive consideration of both scheduling and heat integration.In this paper,the mixed integer nonlinear programming(MINLP) mathematical model of multi-product plant heat integration optimization with the goal of energy-saving annual profit(EAP) is established.The simultaneous optimization and sequential optimization are carried out respectively by bi-level programming(BP) based on the genetic algorithm(GA),and the calculation results are compared.EAP better captures the trade-off relationship between scheduling schemes,energy-saving profits,and equipment costs.The bi-level programming approach based on GA categorizes variables into integer and real types,enabling structural optimization and parameter optimization of the heat exchanger network.This,in turn,enhances solution efficiency and overcomes the limitations of conventional optimization algorithms in terms of solution speed and quality.Two examples show that the EAP of indirect heat integration considering the storage tank are 21% and 2% higher than that of the direct heat integration,and EAP of the simultaneous optimization are26% and 6% higher than that of the sequential optimization.The example demonstrates that the model and algorithm are applicable to batch multi-product plants,such as those in the chemical,pharmaceutical,and food industries,and possess strong practicality and innovation.展开更多
基金Project(2009GK2009) supported by Science and Technology Department Funds of Hunan Province,ChinaProject(08C26224302178) supported by Innovation Fund for Technology Based Firms of China
文摘Taking the ratio of heat transfer area to net power and heat recovery efficiency into account, a multi-objective mathematical model was developed for organic Rankine cycle （ORC）. Working fluids considered were R123, R134a, R141b, R227ea and R245fa. Under the given conditions, the parameters including evaporating and condensing pressures, working fluid and cooling water velocities were optimized by simulated annealing algorithm. The results show that the optimal evaporating pressure increases with the heat source temperature increasing. Compared with other working fluids, R123 is the best choice for the temperature range of 100--180℃ and R141 b shows better performance when the temperature is higher than 180 ℃. Economic characteristic of system decreases rapidly with the decrease of heat source temperature. ORC system is uneconomical for the heat source temperature lower than 100℃.
基金financial support from the National Natural Science Foundation of China (21706220)
文摘Multivariate statistical process monitoring methods are often used in chemical process fault diagnosis.In this article,(I)the cycle temporal algorithm(CTA)combined with the dynamic kernel principal component analysis(DKPCA)and the multiway dynamic kernel principal component analysis(MDKPCA)fault detection algorithms are proposed,which are used for continuous and batch process fault detections,respectively.In addition,(II)a fault variable identification model based on reconstructed-based contribution(RBC)model that paves the way for determining the cause of the fault are proposed.The proposed fault diagnosis model was applied to Tennessee Eastman(TE)process and penicillin fermentation process for fault diagnosis.And compare with other fault diagnosis methods.The results show that the proposed method has better detection effects than other methods.Finally,the reconstruction-based contribution(RBC)model method is used to accurately locate the root cause of the fault and determine the fault path.
基金This Research was Financially Supported by Faculty of Engineering,Mahasarakham University(Grant year 2021).
文摘This paper proposes a low complexity control scheme for voltage control of a dynamic voltage restorer(DVR)in a three-phase system.The control scheme employs the fractional order,proportional-integral-derivative(FOPID)controller to improve on the DVR performance in order to enhance the power quality in terms of the response time,steady-state error and total harmonic distortion(THD).The result obtained was compared with fractional order,proportionalintegral(FOPI),proportional-integral-derivative(PID)and proportional-integral(PI)controllers in order to show the effectiveness of the proposed DVR control scheme.A water cycle optimization algorithm(WCA)was utilized to find the optimal set for all the controller gains.They were used to solve four power quality issues;balanced voltage sag,balanced voltage swell,unbalanced voltage sag,and unbalanced voltage swell.It showed that one set of controller gain obtained from the WCA could solve all the power quality issues while the others in the literature needed an individual set of optimal gain for each power quality problem.To prove the concept,the proposed DVR algorithm was simulated in the MATLAB/Simulink software and the results revealed that the four optimal controllers can compensate for all the power quality problems.A comparative analysis of the results in various aspects of their dynamic response and%THD was discussed and analyzed.It was found that PID controller yields the most rapid performance in terms of average response time while FOPID controller yields the best performance in term of average%steady-state error.FOPI controller was found to provide the lowest THD percentage in the average%THD.FOPID did not differ much in average response from the PID and average%THD from FOPI;however,FOPID provided the most outstanding average steady-state error.According to the CBMA curve,the dynamic responses of all controllers fall in the acceptable power quality area.The total harmonic distortion(THD)of the compensated load voltage from all the controllers were within the 8%limit in accordance to the IEEE std.519-2014.
基金supported by the National Natural Science Foundation of China[Grant No.12461035]Qinghai University Students Innovative Training Program Project[2024-QX-57].
文摘Wind farm layout optimization is a critical challenge in renewable energy development,especially in regions with complex terrain.Micro-siting of wind turbines has a significant impact on the overall efficiency and economic viability of wind farm,where the wake effect,wind speed,types of wind turbines,etc.,have an impact on the output power of the wind farm.To solve the optimization problem of wind farm layout under complex terrain conditions,this paper proposes wind turbine layout optimization using different types of wind turbines,the aim is to reduce the influence of the wake effect and maximize economic benefits.The linear wake model is used for wake flow calculation over complex terrain.Minimizing the unit energy cost is taken as the objective function,considering that the objective function is affected by cost and output power,which influence each other.The cost function includes construction cost,installation cost,maintenance cost,etc.Therefore,a bi-level constrained optimization model is established,in which the upper-level objective function is to minimize the unit energy cost,and the lower-level objective function is to maximize the output power.Then,a hybrid evolutionary algorithm is designed according to the characteristics of the decision variables.The improved genetic algorithm and differential evolution are used to optimize the upper-level and lower-level objective functions,respectively,these evolutionary operations search for the optimal solution as much as possible.Finally,taking the roughness of different terrain,wind farms of different scales and different types of wind turbines as research scenarios,the optimal deployment is solved by using the algorithm in this paper,and four algorithms are compared to verify the effectiveness of the proposed algorithm.
基金Supported by China Mobile Research Institute and China National S&T Major Project(2010ZX03003-003)
文摘An effective Luby transform （LT） encoding algorithm based on short cycle elimination is proposed to improve decoding probabilities of short length LT codes. By searching the generator ma- trix, some special encoded symbols are generated by the encoder to effectively break the short cycles that have negative effect on the performance of LT codes. Analysis and numerical results show that by employing the proposed algorithm, the encoding complexity decreases and the decoding probabili- ties improve both in binary erasure channels （BECs） and additive white gauss noise （AWGN） chan- nels.
文摘We put forward an alternative quantum algorithm for finding ttamiltonian cycles in any N-vertex graph based on adiabatic quantum computing. With a yon Neumann measurement on the final state, one may determine whether there is a HamiRonian cycle in the graph and pick out a cycle if there is any. Although the proposed algorithm provides a quadratic speedup, it gives an alternative algorithm based on adiabatic quantum computation, which is of interest because of its inherent robustness.
文摘铁路光传送网络是高速铁路地面基础设施的神经中枢,为避免网络故障给铁路运营带来巨大损失,重点研究光传送网P-Cycle(Pre-configured Cycle)保护技术,提出在圈扩展时以所有候选圈上未保护工作容量的方差、冗余度两个指标为比较标准的RVPA(Redundancy and Variance Based P-Cycle Construction Algorithm)算法。圈扩展的过程中,算法将选择方差与冗余度能同时满足条件的候选圈作为本轮扩展圈,有效限制了完成保护的P-Cycle圈个数;圈扩展停止条件中,当UPL与参数M、冗余度的大小关系满足条件时,则停止圈扩展,从而限制圈上节点数,使圈个数与圈长度得到有效均衡;在仿真过程中,利用泛欧网络拓扑COST239对RVPA算法进行仿真,并对比分析不同M值下的性能。仿真结果表明,在相同空闲资源与待保护工作容量设定下,参数M取0.5时效果最优,并且RVPA算法的保护容量效率、所需圈的个数、算法整体耗时、总冗余度均优于已有的POCA(P-Cycle Optimization Configuration Heuristic Algorithm)算法。
基金The National Natural Science Foundation of China(No.50978057)the National Key Technology R& D Program of China duringthe 11th Five-Year Plan Period (No.2006BAJ18B03)+1 种基金the Scientific Research Foundation of Graduate School of Southeast University ( No.YBJJ1013)the Program for Postgraduates Research Innovation in University of Jiangsu Province(No.CX09B 060Z)
文摘Due to the fact that headway is a key factor to be considered in bus scheduling, this paper proposes a bi-level programming model for optimizing bus headway in public transit lines. In this model, with the interests of bus companies and passengers in mind, the upper-level model＇s objective is to minimize the total cost, which is affected by frequency settings, both in time and economy in the transit system. The lower-level model is a transit assignment model used to describe the assignment of passengers＇ trips to the network based on the optimal bus headway. In order to solve the proposed model, a hybrid genetic algorithm, namely the genetic algorithm and the simulated annealing algorithm （GA-SA）, is designed. Finally, the model and the algorithm are tested against the transit data, by taking some of the bus lines of Changzhou city as an example. Results indicate that the proposed model allows supply and demand to be linked, which is reasonable, and the solving algorithm is effective.
文摘Based on genetic algorithms, a solution algorithm is presented for the bi-level decision making problem with continuous variables in the upper level in accordance with the bi-level decision making principle. The algorithm is compared with Monte Carlo simulated annealing algorithm, and its feasibility and effectiveness are verified with two calculating examples.
文摘A genetic-fuzzy HEV control strategy based on driving cycle recognition （DCR） was built. Six driving cycles were selected to represent different traffic conditions e.g. freeway, urban, suburb. A neural algorithm was used for traffic condition recognition based on ten parameters of each driving cycle. The DCR was utilized for optimization of the HEV control parameters using a genetic-fuzzy approach. A fuzzy logic controller （FLC） was designed to be intelligent to manage the engine to work in the vicinity of its optimal condition. The fuzzy membership function parameters were optimized using the genetic algorithm （GA） for each driving cycle. The result is that the DCR_ fuzzy controller can reduce the fuel consumption by 1. 9%, higher than only CYC _ HWFET optimized fuzzy （0.2%） or CYC _ WVUSUB optimized fuzzy （0.7%）. The DCR_ fuzzy method can get the better result than only optimizing one cycle on the complex real traffic conditions.
基金the support provided by Ford Foundation,Stanford SCID and National Planning Office of Philosophy and Social Science(Approval No.12 & ZD038)
文摘In reference to the method of the Conference Board,the coincident indexes for China are constructed from a sample period between January 1990 and May 2012 and by51 chosen component indicators.The resulting coincident indexes have higher correlations with gross domestic product(GDP) growth rates than the China Economic Monitoring and Analysis Center(CEMAC) coincident index over the sample period between February2005 and May 2012.The peaks and troughs of the growth rates in several indicators are identified.The total number of peaks and troughs in the resulting coincident index is the same with the CEMAC coincident index.Unfortunately,these troughs don't signify recessions in the Chinese economy because the financial system has not seen a negative growth rate over the specific sample periods.The impacts of the Southeast Asian Financial Crisis and subprime mortgage crisis on the business cycle could be dated via a smoother index from HP filtering to the coincident index.
基金the support of the National BioResource Project(NIG,Japan):E.coli Strain for kindly providing us with the Keio Collection using for our experimental sectionAlso this work is funded by Vicerrectoria de investigaciones at Universidad de los Andes.
文摘In silico approaches for metabolites optimization have been derived from the flood of sequenced and annotated genomes. However, there exist still numerous degrees of freedom in terms of optimization algorithm approaches that can be exploited in order to enhance yield of processes which are based on biological reactions. Here, we propose an evolutionary approach aiming to suggest different mutant for augmenting ethanol yield using glycerol as substrate in Escherichia coli. We found that this algorithm, even though is far from providing the global optimum, is able to uncover genes that a global optimizer would be incapable of. By over-expressing accB, eno, dapE, and accA mutants in ethanol production was augmented up to 2 fold compared to its counterpart E. coli BW25113.
文摘The research on scheduling and heat integration of batch process plays an important role in reducing energy consumption,improving production efficiency and enhancing the competitiveness of industries.The complexity and difficulty of the model solving are increased due to the comprehensive consideration of both scheduling and heat integration.In this paper,the mixed integer nonlinear programming(MINLP) mathematical model of multi-product plant heat integration optimization with the goal of energy-saving annual profit(EAP) is established.The simultaneous optimization and sequential optimization are carried out respectively by bi-level programming(BP) based on the genetic algorithm(GA),and the calculation results are compared.EAP better captures the trade-off relationship between scheduling schemes,energy-saving profits,and equipment costs.The bi-level programming approach based on GA categorizes variables into integer and real types,enabling structural optimization and parameter optimization of the heat exchanger network.This,in turn,enhances solution efficiency and overcomes the limitations of conventional optimization algorithms in terms of solution speed and quality.Two examples show that the EAP of indirect heat integration considering the storage tank are 21% and 2% higher than that of the direct heat integration,and EAP of the simultaneous optimization are26% and 6% higher than that of the sequential optimization.The example demonstrates that the model and algorithm are applicable to batch multi-product plants,such as those in the chemical,pharmaceutical,and food industries,and possess strong practicality and innovation.
