Heat integration is important for energy-saving in the process industry.It is linked to the persistently challenging task of optimal design of heat exchanger networks(HEN).Due to the inherent highly nonconvex nonlinea...Heat integration is important for energy-saving in the process industry.It is linked to the persistently challenging task of optimal design of heat exchanger networks(HEN).Due to the inherent highly nonconvex nonlinear and combinatorial nature of the HEN problem,it is not easy to find solutions of high quality for large-scale problems.The reinforcement learning(RL)method,which learns strategies through ongoing exploration and exploitation,reveals advantages in such area.However,due to the complexity of the HEN design problem,the RL method for HEN should be dedicated and designed.A hybrid strategy combining RL with mathematical programming is proposed to take better advantage of both methods.An insightful state representation of the HEN structure as well as a customized reward function is introduced.A Q-learning algorithm is applied to update the HEN structure using theε-greedy strategy.Better results are obtained from three literature cases of different scales.展开更多
The steelmaking process scheduling problem by considering variable electricity price （SMSPVEP） was in- vestigated. A decomposition approach was proposed for the SMSPVEP. At the first stage, mathematical program-ming...The steelmaking process scheduling problem by considering variable electricity price （SMSPVEP） was in- vestigated. A decomposition approach was proposed for the SMSPVEP. At the first stage, mathematical program-ming was utilized to minimize the maximum completion time for each cast without considering variable electricity price. At the second stage, based on obtained relative schedules of all casts, a mathematical model was formulated with an objective of minimizing the energy cost for all casts scheduling problem. The two-stage models were tested on randomly generated instances based on the practical process in a Chinese steelmaking plant. Computational results demonstrate the effectiveness of the proposed approach.展开更多
In this contribution we present an online scheduling algorithm for a real world multiproduct batch plant. The overall mixed integer nonlinear programming (MINLP) problem is hierarchically structured into a mixed integ...In this contribution we present an online scheduling algorithm for a real world multiproduct batch plant. The overall mixed integer nonlinear programming (MINLP) problem is hierarchically structured into a mixed integer linear programming (MILP) problem first and then a reduced dimensional MINLP problem, which are optimized by mathematical programming (MP) and genetic algorithm (GA) respectively. The basis idea relies on combining MP with GA to exploit their complementary capacity. The key features of the hierarchical model are explained and illustrated with some real world cases from the multiproduct batch plants.展开更多
Bilinear theological lubrication mechanics provides an important basis for the designs of re- cently developed electrorheological(ER)'smart'journal bearings and those lubricated by mixed fluid-solid lubri- can...Bilinear theological lubrication mechanics provides an important basis for the designs of re- cently developed electrorheological(ER)'smart'journal bearings and those lubricated by mixed fluid-solid lubri- cants.But there is not yet a reliable and efficient numerical method for such a problem of non-Newtonian flu- id mechanics.In the present paper,a finite element method(FEM)together with mat hematical programming solution is successfully used to solve such a problem.A reliable and generalized numerical method for the designs of electrorheological 'smart' journal bearings and the bearings lubricated by mixed fluid- solid lubri- cant is presented.展开更多
In this paper,a multi-objective sustainable biomass supply chain network under uncertainty is designed by neutrosophic programming method.In this method,for each objective function of the problem,three functions of tr...In this paper,a multi-objective sustainable biomass supply chain network under uncertainty is designed by neutrosophic programming method.In this method,for each objective function of the problem,three functions of truth membership,non-determination and falsehood are considered.Neutrosophic programming method in this paper simultaneously seeks to optimize the total costs of the supply chain network,the amount of greenhouse gas emissions,the number of potential people hired and the time of product transfer along the supply chain network.To achieve the stated objective functions,strategic decisions such as locating potential facilities and tactical decisions such as optimal product flow allocation and vehicle routing must be made.The results of the implementation of neutrosophic programming method show the high efficiency of this method in achieving the optimal values of each objective function.Also,by examining the rate of uncertainty,it was observed that with increasing this rate,the total costs of supply chain network design,greenhouse gas emissions and product transfer times have increased,and in contrast,the potential employment rate of individuals has decreased.展开更多
This paper is based on the finite and dispersed data which were obtained from the experiments of the wind tunnel and of the force measurement and from the high-speed photography. It analyses and optimizes the take-off...This paper is based on the finite and dispersed data which were obtained from the experiments of the wind tunnel and of the force measurement and from the high-speed photography. It analyses and optimizes the take-off movement of ski jumping with the theory of dynamics of systems of rigid bodies and with the method of mathematical programming. The paper describes the optimal take-off movement of ski jumping. Furthermore, it presents an example and compares the result with those of other papers published at home and abroad. The comparison shows that our computation and optimization are reasonable and well-grounded.展开更多
By expanding the yielding function according toTaylor series and neglecting the high order terms, the elastoplastic constitutive equation is written in a linear complementary form. Based on this linear complementary f...By expanding the yielding function according toTaylor series and neglecting the high order terms, the elastoplastic constitutive equation is written in a linear complementary form. Based on this linear complementary form and the principle of virtual work, a finite element-complementary method is derived for elastoplastic problem. This method is available for materials which satisfy either associated or nonassociated flow rule. In addition, the existence and uniqueness oj solution for the method are also discussed and some useful conclusions are given.展开更多
A fuzzy bi-matrix game（FBG）,namely a two-person non-zero-sum game with fuzzy strategies and fuzzy payoffs is proposed.We have defined and analyzed the optimal strategies of this FBG,and shown that it can be transfor...A fuzzy bi-matrix game（FBG）,namely a two-person non-zero-sum game with fuzzy strategies and fuzzy payoffs is proposed.We have defined and analyzed the optimal strategies of this FBG,and shown that it can be transformed into a corresponding fuzzy mathematical programming issue,for which a ranking function approach can be applied.In addition,optimal strategies of FBG for both Player I and Player II can be gotten.展开更多
This paper deals with the limit analyses of perfect rigid-plastic continua.Based on the kinematic theorem of the limit analysis theory,a mathematical programming finite element formula for determining the upper bound ...This paper deals with the limit analyses of perfect rigid-plastic continua.Based on the kinematic theorem of the limit analysis theory,a mathematical programming finite element formula for determining the upper bound load multiplier has been established,and an iteration algorithm proposed accordingly.In this algorithm the plastic and rigid zones are distinguished for every iteration step,and the goal function is modified gradually.The difficulties caused by the nonsmoothness of the goal function are over- come.Some examples solved by this algorithm are presented.展开更多
In addition to the conventional methods of the calibration model construction, such as PCR （principal components regression） and PLS （partial least-squares）, a MPM （mathematical programming method） is developed ...In addition to the conventional methods of the calibration model construction, such as PCR （principal components regression） and PLS （partial least-squares）, a MPM （mathematical programming method） is developed and proposed for practical use in NIR analyses of agricultural and food products. The proposed method involves the mathematical programming techniques to seek the regression coefficients for the calibration model calculation. It is based on the optimization theory used for finding the extremum of the objective function in the given domain of a vector space and employs the method of the complementarity problems solving. The MPM algorithm is described in detail. The MPM was tested on an InfraLUM FT-10 NIR analyzer of Lumex company with samples of dry milk （for fat）, corn （for protein） and rye flour （for moisture）. The obtained results show that the MPM can be used for constructing multivariate calibrations with the qualitative characteristics superior over those of the classical PCR and PLS methods of analysis.展开更多
The study deals with the multi-choice mathematical programming problem, where the right hand side of the constraints is multi-choice in nature. However, the problem of multi-choice linear programming cannot be solved ...The study deals with the multi-choice mathematical programming problem, where the right hand side of the constraints is multi-choice in nature. However, the problem of multi-choice linear programming cannot be solved directly by standard linear or nonlinear programming techniques. The aim of this paper is to transform such problems to a standard mathematical linear programming problem. For each constraint, exactly one parameter value is selected out of a multiple number of parameter values. This process of selection can be established in different ways. In this paper, we present a new simple technique enabling us to handle such problem as a mixed integer linear programming problem and consequently solve them by using standard linear programming software. Our main aim depends on inserting a specific number of binary variables and using them to construct a linear combination which gives just one parameter among the multiple choice values for each choice of the values of the binary variables. A numerical example is presented to illustrate our analysis.展开更多
We study in this paper a mathematical programming model for the coexistence of competitions and cooperations problems. We introduce a new solution concept, s-optimal solution for the problem, which always exists under...We study in this paper a mathematical programming model for the coexistence of competitions and cooperations problems. We introduce a new solution concept, s-optimal solution for the problem, which always exists under compact and continuous conditions. It is shown that an s-optimal solution can be obtained by solving a nonlinear programming problem. Some examples are given to explain how to compute an s-optimal solution.展开更多
The gate assignment at an airport is one of the major activities in airport operations.With the increase of passenger traffic volumes and the number of flights, the complexity of this task and the factors to be consid...The gate assignment at an airport is one of the major activities in airport operations.With the increase of passenger traffic volumes and the number of flights, the complexity of this task and the factors to be considered have increased significantly, and an efficient gate utilizationhas received considerable attention. For overcoming the shortcomings of previous gate assignmentapproaches, this paper presents a partial parallel gate assignment approach, by which more factorsconcerning aircraft and gates can be collsidered at the same time. This paper also presents themethod of using a knowledge-based system combined with a mathematical programming method forgetting an optimized feasible assignment solution. By this way, it is more easily to get the solutionthat satisfies both the static and dynamic situations,and thus it may adapt well to meet the needsof actual use to rea-time operations. An experimental prototype has been implemented, and a casestudy is presented at the end of the paper.展开更多
This paper presents a procedure for designing a supplementary damping stabilizer for a static synchronous series compensator(SSSC) in multi-machine power systems.The objective is to shift the lightly damped inter-area...This paper presents a procedure for designing a supplementary damping stabilizer for a static synchronous series compensator(SSSC) in multi-machine power systems.The objective is to shift the lightly damped inter-area modes toward the prescribed stability region.A lead-lag stabilizer is used to demonstrate this technique,in which a particular measure of stabilizer gain is considered as an objective function.Constraints of the problem for phase-lead and lag structures are derived.The objective function with the constraints is formed as a quadratic mathematical programming problem.For robust design,the parameters of the stabilizer are calculated under various operating conditions.Two types of SSSC-based stabilizer have been presented and designed.Numerical results including eigenvalue analysis and the nonlinear simulations on the 4-and 50-machine power systems are pre-sented to show the effectiveness of the proposed method.展开更多
The optimal experimental methods of a multidimensional dynamic programming,a large-scale linear and a complex nonlinear system are presented,which achieve a great step forward in the field of systems science.And excel...The optimal experimental methods of a multidimensional dynamic programming,a large-scale linear and a complex nonlinear system are presented,which achieve a great step forward in the field of systems science.And excellent results are obtained in the applications of complex water resource systems.展开更多
this paper,we propose a class of smoothing-regularization methods for solving the mathematical programming with vanishing constraints.These methods include the smoothing-regularization method proposed by Kanzow et al....this paper,we propose a class of smoothing-regularization methods for solving the mathematical programming with vanishing constraints.These methods include the smoothing-regularization method proposed by Kanzow et al.in[Comput.Optim.Appl.,2013,55(3):733-767]as a special case.Under the weaker conditions than the ones that have been used by Kanzow et al.in 2013,we prove that the Mangasarian-Fromovitz constraint qualification holds at the feasible points of smoothing-regularization problem.We also analyze that the convergence behavior of the proposed smoothing-regularization method under mild conditions,i.e.,any accumulation point of the stationary point sequence for the smoothing-regularization problem is a strong stationary point.Finally,numerical experiments are given to show the efficiency of the proposed methods.展开更多
Conceptual process design (CPD) research focuses on finding design alternatives that address various design problems. It has a long history of well-established methodologies to answer these complex questions, such as ...Conceptual process design (CPD) research focuses on finding design alternatives that address various design problems. It has a long history of well-established methodologies to answer these complex questions, such as heuristics, mathematical programming, and pinch analysis. Nonetheless, progress continues from different formulations of design problems using bottom-up approaches, to the utilization of new tools such as artificial intelligence (AI). It was not until recently that AI methods were involved again in assisting the decision-making steps for chemical engineers. This has led to a gap in understanding AI's capabilities and limitations within the field of CPD research. Thus, this article aims to provide an overview of conventional methods for process synthesis, integration, and intensification approaches and survey emerging AI-assisted process design applications to bridge the gap. A review of all AI-assisted methods is highlighted, where AI is used as a key component within a design framework, to explain the utility of AI with comparative examples. The studies were categorized into supervised and reinforcement learning based on the machine learning training principles they used to enhance the understanding of requirements, benefits, and challenges that come with it. Furthermore, we provide challenges and prospects that can facilitate or hinder the progress of AI-assisted approaches in the future.展开更多
A quadratic programming model is established to choose the blocks to be blasted in a given period. The length of this period depends on the production planning requirements. During the given period, the blocks' pa...A quadratic programming model is established to choose the blocks to be blasted in a given period. The length of this period depends on the production planning requirements. During the given period, the blocks' parameters are available from the geological database of the mine. The objective is to minimize the deviation of the average ore grade of blasted blocks from the standard ore grade required by the mill. Transportation ability constraint. production quantity demand constraint. minimum safety bench constraint. block size constraint and block, bench precedence constraints are considered in forming the programming model. This model has more practical objective function and reasonable constraints compared with the existing model for this kind of problems.展开更多
Airborne laser scanning(ALS)has been widely applied to estimate tree and forest attributes,but it can also drive the segmentation of forest areas.Clustering algorithms are the dominant technique in segmentation but sp...Airborne laser scanning(ALS)has been widely applied to estimate tree and forest attributes,but it can also drive the segmentation of forest areas.Clustering algorithms are the dominant technique in segmentation but spatial optimization using exact methods remains untested.This study presents a novel approach to segmentation based on mixed integer programming to create forest management units(FMUs).This investigation focuses on using raster information derived from ALS surveys.Two mainstream clustering algorithms were compared to the new MIP formula that simultaneously accounts for area and adjacency restrictions,FMUs size and homogeneity in terms of vegetation height.The optimal problem solution was found when using less than 150 cells,showing the problem formulation is solvable.The results for MIP were better than for the clustering algorithms;FMUs were more compact based on the intravariation of canopy height and the variability in size was lower.The MIP model allows the user to strictly control the size of FMUs,which is not possible in heuristic optimization and in the clustering algorithms tested.The definition of forest management units based on remote sensing data is an important operation and our study pioneers the use of MIP ALS-based optimal segmentation.展开更多
Perzyna model in viscoplasticity has been studied by the parametric variational principle, which could be transformed into solving the parametric quadratic programming problem. The FEM form of this problem and its imp...Perzyna model in viscoplasticity has been studied by the parametric variational principle, which could be transformed into solving the parametric quadratic programming problem. The FEM form of this problem and its implementation have also been discussed in the paper.展开更多
基金The financial support provided by the Project of National Natural Science Foundation of China(U22A20415,21978256,22308314)“Pioneer”and“Leading Goose”Research&Development Program of Zhejiang(2022C01SA442617)。
文摘Heat integration is important for energy-saving in the process industry.It is linked to the persistently challenging task of optimal design of heat exchanger networks(HEN).Due to the inherent highly nonconvex nonlinear and combinatorial nature of the HEN problem,it is not easy to find solutions of high quality for large-scale problems.The reinforcement learning(RL)method,which learns strategies through ongoing exploration and exploitation,reveals advantages in such area.However,due to the complexity of the HEN design problem,the RL method for HEN should be dedicated and designed.A hybrid strategy combining RL with mathematical programming is proposed to take better advantage of both methods.An insightful state representation of the HEN structure as well as a customized reward function is introduced.A Q-learning algorithm is applied to update the HEN structure using theε-greedy strategy.Better results are obtained from three literature cases of different scales.
基金Item Sponsored by National Natural Science Foundation of China (71171038,71021061 )Fundamental Research Funds for Central Universities of China (N100504001)
文摘The steelmaking process scheduling problem by considering variable electricity price （SMSPVEP） was in- vestigated. A decomposition approach was proposed for the SMSPVEP. At the first stage, mathematical program-ming was utilized to minimize the maximum completion time for each cast without considering variable electricity price. At the second stage, based on obtained relative schedules of all casts, a mathematical model was formulated with an objective of minimizing the energy cost for all casts scheduling problem. The two-stage models were tested on randomly generated instances based on the practical process in a Chinese steelmaking plant. Computational results demonstrate the effectiveness of the proposed approach.
基金Supported by the National 973 Program of China (No. G2000263).
文摘In this contribution we present an online scheduling algorithm for a real world multiproduct batch plant. The overall mixed integer nonlinear programming (MINLP) problem is hierarchically structured into a mixed integer linear programming (MILP) problem first and then a reduced dimensional MINLP problem, which are optimized by mathematical programming (MP) and genetic algorithm (GA) respectively. The basis idea relies on combining MP with GA to exploit their complementary capacity. The key features of the hierarchical model are explained and illustrated with some real world cases from the multiproduct batch plants.
文摘Bilinear theological lubrication mechanics provides an important basis for the designs of re- cently developed electrorheological(ER)'smart'journal bearings and those lubricated by mixed fluid-solid lubri- cants.But there is not yet a reliable and efficient numerical method for such a problem of non-Newtonian flu- id mechanics.In the present paper,a finite element method(FEM)together with mat hematical programming solution is successfully used to solve such a problem.A reliable and generalized numerical method for the designs of electrorheological 'smart' journal bearings and the bearings lubricated by mixed fluid- solid lubri- cant is presented.
文摘In this paper,a multi-objective sustainable biomass supply chain network under uncertainty is designed by neutrosophic programming method.In this method,for each objective function of the problem,three functions of truth membership,non-determination and falsehood are considered.Neutrosophic programming method in this paper simultaneously seeks to optimize the total costs of the supply chain network,the amount of greenhouse gas emissions,the number of potential people hired and the time of product transfer along the supply chain network.To achieve the stated objective functions,strategic decisions such as locating potential facilities and tactical decisions such as optimal product flow allocation and vehicle routing must be made.The results of the implementation of neutrosophic programming method show the high efficiency of this method in achieving the optimal values of each objective function.Also,by examining the rate of uncertainty,it was observed that with increasing this rate,the total costs of supply chain network design,greenhouse gas emissions and product transfer times have increased,and in contrast,the potential employment rate of individuals has decreased.
基金Project supported by the National Natutal Science Foundation of China
文摘This paper is based on the finite and dispersed data which were obtained from the experiments of the wind tunnel and of the force measurement and from the high-speed photography. It analyses and optimizes the take-off movement of ski jumping with the theory of dynamics of systems of rigid bodies and with the method of mathematical programming. The paper describes the optimal take-off movement of ski jumping. Furthermore, it presents an example and compares the result with those of other papers published at home and abroad. The comparison shows that our computation and optimization are reasonable and well-grounded.
文摘By expanding the yielding function according toTaylor series and neglecting the high order terms, the elastoplastic constitutive equation is written in a linear complementary form. Based on this linear complementary form and the principle of virtual work, a finite element-complementary method is derived for elastoplastic problem. This method is available for materials which satisfy either associated or nonassociated flow rule. In addition, the existence and uniqueness oj solution for the method are also discussed and some useful conclusions are given.
基金Sponsored by the National Natural Science Foundation of China(70471063,70771010)
文摘A fuzzy bi-matrix game（FBG）,namely a two-person non-zero-sum game with fuzzy strategies and fuzzy payoffs is proposed.We have defined and analyzed the optimal strategies of this FBG,and shown that it can be transformed into a corresponding fuzzy mathematical programming issue,for which a ranking function approach can be applied.In addition,optimal strategies of FBG for both Player I and Player II can be gotten.
基金The project supported by National Natural Science Foundation of China.
文摘This paper deals with the limit analyses of perfect rigid-plastic continua.Based on the kinematic theorem of the limit analysis theory,a mathematical programming finite element formula for determining the upper bound load multiplier has been established,and an iteration algorithm proposed accordingly.In this algorithm the plastic and rigid zones are distinguished for every iteration step,and the goal function is modified gradually.The difficulties caused by the nonsmoothness of the goal function are over- come.Some examples solved by this algorithm are presented.
文摘In addition to the conventional methods of the calibration model construction, such as PCR （principal components regression） and PLS （partial least-squares）, a MPM （mathematical programming method） is developed and proposed for practical use in NIR analyses of agricultural and food products. The proposed method involves the mathematical programming techniques to seek the regression coefficients for the calibration model calculation. It is based on the optimization theory used for finding the extremum of the objective function in the given domain of a vector space and employs the method of the complementarity problems solving. The MPM algorithm is described in detail. The MPM was tested on an InfraLUM FT-10 NIR analyzer of Lumex company with samples of dry milk （for fat）, corn （for protein） and rye flour （for moisture）. The obtained results show that the MPM can be used for constructing multivariate calibrations with the qualitative characteristics superior over those of the classical PCR and PLS methods of analysis.
文摘The study deals with the multi-choice mathematical programming problem, where the right hand side of the constraints is multi-choice in nature. However, the problem of multi-choice linear programming cannot be solved directly by standard linear or nonlinear programming techniques. The aim of this paper is to transform such problems to a standard mathematical linear programming problem. For each constraint, exactly one parameter value is selected out of a multiple number of parameter values. This process of selection can be established in different ways. In this paper, we present a new simple technique enabling us to handle such problem as a mixed integer linear programming problem and consequently solve them by using standard linear programming software. Our main aim depends on inserting a specific number of binary variables and using them to construct a linear combination which gives just one parameter among the multiple choice values for each choice of the values of the binary variables. A numerical example is presented to illustrate our analysis.
基金This research is supported by the National Natural Science Foundation of China under grunt 70271021 and SRG7001150.
文摘We study in this paper a mathematical programming model for the coexistence of competitions and cooperations problems. We introduce a new solution concept, s-optimal solution for the problem, which always exists under compact and continuous conditions. It is shown that an s-optimal solution can be obtained by solving a nonlinear programming problem. Some examples are given to explain how to compute an s-optimal solution.
文摘The gate assignment at an airport is one of the major activities in airport operations.With the increase of passenger traffic volumes and the number of flights, the complexity of this task and the factors to be considered have increased significantly, and an efficient gate utilizationhas received considerable attention. For overcoming the shortcomings of previous gate assignmentapproaches, this paper presents a partial parallel gate assignment approach, by which more factorsconcerning aircraft and gates can be collsidered at the same time. This paper also presents themethod of using a knowledge-based system combined with a mathematical programming method forgetting an optimized feasible assignment solution. By this way, it is more easily to get the solutionthat satisfies both the static and dynamic situations,and thus it may adapt well to meet the needsof actual use to rea-time operations. An experimental prototype has been implemented, and a casestudy is presented at the end of the paper.
文摘This paper presents a procedure for designing a supplementary damping stabilizer for a static synchronous series compensator(SSSC) in multi-machine power systems.The objective is to shift the lightly damped inter-area modes toward the prescribed stability region.A lead-lag stabilizer is used to demonstrate this technique,in which a particular measure of stabilizer gain is considered as an objective function.Constraints of the problem for phase-lead and lag structures are derived.The objective function with the constraints is formed as a quadratic mathematical programming problem.For robust design,the parameters of the stabilizer are calculated under various operating conditions.Two types of SSSC-based stabilizer have been presented and designed.Numerical results including eigenvalue analysis and the nonlinear simulations on the 4-and 50-machine power systems are pre-sented to show the effectiveness of the proposed method.
基金supported hy the National Natural Science Foundation of China(Grant No 79400011)the 333 Engineering Foundation of Jhiangsu Province of China.
文摘The optimal experimental methods of a multidimensional dynamic programming,a large-scale linear and a complex nonlinear system are presented,which achieve a great step forward in the field of systems science.And excellent results are obtained in the applications of complex water resource systems.
基金Supported in part by NSFC(No.11961011)Guangxi Science and Technology Base and Talents Special Project(No.2021AC06001).
文摘this paper,we propose a class of smoothing-regularization methods for solving the mathematical programming with vanishing constraints.These methods include the smoothing-regularization method proposed by Kanzow et al.in[Comput.Optim.Appl.,2013,55(3):733-767]as a special case.Under the weaker conditions than the ones that have been used by Kanzow et al.in 2013,we prove that the Mangasarian-Fromovitz constraint qualification holds at the feasible points of smoothing-regularization problem.We also analyze that the convergence behavior of the proposed smoothing-regularization method under mild conditions,i.e.,any accumulation point of the stationary point sequence for the smoothing-regularization problem is a strong stationary point.Finally,numerical experiments are given to show the efficiency of the proposed methods.
基金financial support from The University of Manchester
文摘Conceptual process design (CPD) research focuses on finding design alternatives that address various design problems. It has a long history of well-established methodologies to answer these complex questions, such as heuristics, mathematical programming, and pinch analysis. Nonetheless, progress continues from different formulations of design problems using bottom-up approaches, to the utilization of new tools such as artificial intelligence (AI). It was not until recently that AI methods were involved again in assisting the decision-making steps for chemical engineers. This has led to a gap in understanding AI's capabilities and limitations within the field of CPD research. Thus, this article aims to provide an overview of conventional methods for process synthesis, integration, and intensification approaches and survey emerging AI-assisted process design applications to bridge the gap. A review of all AI-assisted methods is highlighted, where AI is used as a key component within a design framework, to explain the utility of AI with comparative examples. The studies were categorized into supervised and reinforcement learning based on the machine learning training principles they used to enhance the understanding of requirements, benefits, and challenges that come with it. Furthermore, we provide challenges and prospects that can facilitate or hinder the progress of AI-assisted approaches in the future.
文摘A quadratic programming model is established to choose the blocks to be blasted in a given period. The length of this period depends on the production planning requirements. During the given period, the blocks' parameters are available from the geological database of the mine. The objective is to minimize the deviation of the average ore grade of blasted blocks from the standard ore grade required by the mill. Transportation ability constraint. production quantity demand constraint. minimum safety bench constraint. block size constraint and block, bench precedence constraints are considered in forming the programming model. This model has more practical objective function and reasonable constraints compared with the existing model for this kind of problems.
基金supported by MODFIRE project—A multiple criteria approach to integrate wildfire behavior in forest management planning(PCIF/MOS/0217/2017)benefited from the research exchange platform provided by the Su Fo Run project(Marie SklodowskaCurie Grant Agreement No.691149)。
文摘Airborne laser scanning(ALS)has been widely applied to estimate tree and forest attributes,but it can also drive the segmentation of forest areas.Clustering algorithms are the dominant technique in segmentation but spatial optimization using exact methods remains untested.This study presents a novel approach to segmentation based on mixed integer programming to create forest management units(FMUs).This investigation focuses on using raster information derived from ALS surveys.Two mainstream clustering algorithms were compared to the new MIP formula that simultaneously accounts for area and adjacency restrictions,FMUs size and homogeneity in terms of vegetation height.The optimal problem solution was found when using less than 150 cells,showing the problem formulation is solvable.The results for MIP were better than for the clustering algorithms;FMUs were more compact based on the intravariation of canopy height and the variability in size was lower.The MIP model allows the user to strictly control the size of FMUs,which is not possible in heuristic optimization and in the clustering algorithms tested.The definition of forest management units based on remote sensing data is an important operation and our study pioneers the use of MIP ALS-based optimal segmentation.
基金The Project Supported by the National Natural Science Foundation of China
文摘Perzyna model in viscoplasticity has been studied by the parametric variational principle, which could be transformed into solving the parametric quadratic programming problem. The FEM form of this problem and its implementation have also been discussed in the paper.
