Chemical batch processes have become significant in chemical manufacturing. In these processes, large numbers of chemical products are produced to satisfy human demands in daily life. Recently, economy globalization h...Chemical batch processes have become significant in chemical manufacturing. In these processes, large numbers of chemical products are produced to satisfy human demands in daily life. Recently, economy globalization has resulted, in growing worldwide competitions in tradi.tional chemical .process industry. In order to keep competitive in the global marketplace, each company must optimize its production management and set up a reactive system for market fluctuation. Scheduling is the core of production management in chemical processes. The goal of this paper is to review the recent developments in this challenging area. Classifications of batch scheduling problems and optimization methods are introduced. A comparison of six typical models is shown in a general benchmark example from the literature. Finally, challenges and applications in future research are discussed.展开更多
It is the fact that several process parameters are either unknown or uncertain. Therefore, an optimal control, profile calculated with developed process models with respect to such process parameters may not give an o...It is the fact that several process parameters are either unknown or uncertain. Therefore, an optimal control, profile calculated with developed process models with respect to such process parameters may not give an optimal performance when implemented to real processes. This study proposes a batch-to-batch optimization strategy for the estimation of uncertain kinetic.par.ameters in a batch crystallization process of potassium sulfate production. The knowledge of a crystal size distribution of the product at the end of batch operation is used in the proposed methodology. The updated kinetic parameters are applied for determining an optimal operating temperature policy for the next batch run.展开更多
In order to solve the flexible job shop scheduling problem with variable batches,we propose an improved multiobjective optimization algorithm,which combines the idea of inverse scheduling.First,a flexible job shop pro...In order to solve the flexible job shop scheduling problem with variable batches,we propose an improved multiobjective optimization algorithm,which combines the idea of inverse scheduling.First,a flexible job shop problem with the variable batches scheduling model is formulated.Second,we propose a batch optimization algorithm with inverse scheduling in which the batch size is adjusted by the dynamic feedback batch adjusting method.Moreover,in order to increase the diversity of the population,two methods are developed.One is the threshold to control the neighborhood updating,and the other is the dynamic clustering algorithm to update the population.Finally,a group of experiments are carried out.The results show that the improved multi-objective optimization algorithm can ensure the diversity of Pareto solutions effectively,and has effective performance in solving the flexible job shop scheduling problem with variable batches.展开更多
An efficient culture medium producing a bacterial elastase with high yields was developed further following preliminary studies by means of response surface method. Central composite design (CCD) and response surface ...An efficient culture medium producing a bacterial elastase with high yields was developed further following preliminary studies by means of response surface method. Central composite design (CCD) and response surface method-ology were applied to optimize the medium constituents. A central composite design was used to explain the combined effect of three medium constituents, viz, glucose, K2HPO4, MgSO47H2O. The strain produced more elastase in the completely optimized medium, as compared with the partially optimized medium. The fitted model of the second model, as per RSM, showed that glucose was 7.4 g/100 ml, casein 1.13 g/100 ml, corn steep flour 0.616 g/100 ml, K2HPO4 0.206 g/100 ml and MgSO47H2O 0.034 g/100 ml. The fermentation kinetics of these two culture media in the flask experiments were analyzed. It was found that the highest elastase productivity occurred at 54 hours. Higher glucose concentration had inhibitory effect on elastase production. At the same time, we observed that the glucose consumption rate was slow in the completely optimized medium, which can explain the lag period of the highest elastase production. Some metal ions and surfactant additives also affected elastase production and cell growth.展开更多
An iterative (run-to-run) optimization method was presented for batch processes under input constraints. Generally it is very difficult to acquire an accurate mechanistic model for a batch process.Because support vect...An iterative (run-to-run) optimization method was presented for batch processes under input constraints. Generally it is very difficult to acquire an accurate mechanistic model for a batch process.Because support vector machine is powerful for the problems characterized by small samples,nonlinearity, high dimension and local minima, support vector regression models were developed for the end-point optimization of batch processes. Since there is no analytical way to find the optimal trajectory, an iterative method was used to exploit the repetitive nature of batch processes to determine the optimal operating policy. The optimization algorithm is proved convergent. The numerical simulation shows that the method can improve the process performance through iterations.展开更多
Batch distillation,basically different from continuous distillation which is a steady stateprocess,appears to be an unsteady state process in its mathematical description.The theoreticalanalysis of its operation compr...Batch distillation,basically different from continuous distillation which is a steady stateprocess,appears to be an unsteady state process in its mathematical description.The theoreticalanalysis of its operation comprises a concomitant consideration of the stage-wise separation andthe equations of material balance as well as enthalpy balance.Based upon the batch distillationpractice of NMP-water system,this paper reveals the necessity and advantage of a computerizedtreatment for this purpose.Numerical results not only explain the experimental phenomena andprovide a design scheme,but also lead to the optimization of the operation condition.展开更多
With the rapid development of intelligent manufacturing and the changes in market demand,the current manufacturing industry presents the characteristics of multi-varieties,small batches,customization,and a short produ...With the rapid development of intelligent manufacturing and the changes in market demand,the current manufacturing industry presents the characteristics of multi-varieties,small batches,customization,and a short production cycle,with the whole production process having certain flexibility.In this paper,a mathematical model is established with the minimum production cycle as the optimization objective for the dual-resource batch scheduling of the flexible job shop,and an improved nested optimization algorithm is designed to solve the problem.The outer layer batch optimization problem is solved by the improved simulated annealing algorithm.The inner double resource scheduling problem is solved by the improved adaptive genetic algorithm,the double coding scheme,and the decoding scheme of Automated Guided Vehicle(AGV)scheduling based on the scheduling rules.The time consumption of collision-free paths is solved with the path planning algorithm which uses the Dijkstra algorithm based on a time window.Finally,the effectiveness of the algorithm is verified by actual cases,and the influence of AGV with different configurations on workshop production efficiency is analyzed.展开更多
This paper employs mathematical modeling and algebraic approach to derive the optimal manufacturing batch size and number of shipment for a vendor-buyer integrated economic production quantity (EPQ) model with scrap. ...This paper employs mathematical modeling and algebraic approach to derive the optimal manufacturing batch size and number of shipment for a vendor-buyer integrated economic production quantity (EPQ) model with scrap. Unlike the conventional method by using differential calculus to determine replenishment lot size and optimal number of shipments for such an integrated system, this paper proposes a straightforward algebraic approach to replace the use of calculus on the total cost function for solving the optimal production- shipment policies. A simpler form for computing long-run average cost for such a vendor- buyer integrated EPQ problem is also provided.展开更多
In this paper, the modelling and multi-objective optimal control of batch processes, using a recurrent neuro-fuzzy network, are presented. The recurrent neuro-fuzzy network, forms a ＂global＂ nonlinear long-range pre...In this paper, the modelling and multi-objective optimal control of batch processes, using a recurrent neuro-fuzzy network, are presented. The recurrent neuro-fuzzy network, forms a ＂global＂ nonlinear long-range prediction model through the fuzzy conjunction of a number of ＂local＂ linear dynamic models. Network output is fed back to network input through one or more time delay units, which ensure that predictions from the recurrent neuro-fuzzy network are long-range. In building a recurrent neural network model, process knowledge is used initially to partition the processes non-linear characteristics into several local operating regions, and to aid in the initialisation of corresponding network weights. Process operational data is then used to train the network. Membership functions of the local regimes are identified, and local models are discovered via network training. Based on a recurrent neuro-fuzzy network model, a multi-objective optimal control policy can be obtained. The proposed technique is applied to a fed-batch reactor.展开更多
This paper presents several neural network based modelling, reliable optimal control, and iterative learning control methods for batch processes. In order to overcome the lack of robustness of a single neural network,...This paper presents several neural network based modelling, reliable optimal control, and iterative learning control methods for batch processes. In order to overcome the lack of robustness of a single neural network, bootstrap aggregated neural networks are used to build reliable data based empirical models. Apart from improving the model generalisation capability, a bootstrap aggregated neural network can also provide model prediction confidence bounds. A reliable optimal control method by incorporating model prediction confidence bounds into the optimisation objective function is presented. A neural network based iterative learning control strategy is presented to overcome the problem due to unknown disturbances and model-plant mismatches. The proposed methods are demonstrated on a simulated batch polymerisation process.展开更多
In this paper,a novel fuzzy neural network model,in which an adjustable fuzzy sub-space was designed by uniform design,has been established and used in fed-batch yeast fermentationas an example.A brand-new optimizatio...In this paper,a novel fuzzy neural network model,in which an adjustable fuzzy sub-space was designed by uniform design,has been established and used in fed-batch yeast fermentationas an example.A brand-new optimization sub-network with special structure has been built andgenetic algorithm,guaranteeing the optimization in overall space,is introduced for the feed rateoptimization.On the basis of the model network,the optimal substrate concentration and theoptimal amount of fed-batch at different periods have been studied,aided with the optimizationnetwork and the genetic algorithm separately.The above results can be used as a basis for theestablishment of a fuzzy neural network controller.展开更多
To improve the productivity,the resource utilization and reduce the production cost of flexible job shops,this paper designs an improved two-layer optimization algorithm for the dual-resource scheduling optimization p...To improve the productivity,the resource utilization and reduce the production cost of flexible job shops,this paper designs an improved two-layer optimization algorithm for the dual-resource scheduling optimization problem of flexible job shop considering workpiece batching.Firstly,a mathematical model is established to minimize the maximum completion time.Secondly,an improved two-layer optimization algorithm is designed:the outer layer algorithm uses an improved PSO(Particle Swarm Optimization)to solve the workpiece batching problem,and the inner layer algorithm uses an improved GA(Genetic Algorithm)to solve the dual-resource scheduling problem.Then,a rescheduling method is designed to solve the task disturbance problem,represented by machine failures,occurring in the workshop production process.Finally,the superiority and effectiveness of the improved two-layer optimization algorithm are verified by two typical cases.The case results show that the improved two-layer optimization algorithm increases the average productivity by 7.44% compared to the ordinary two-layer optimization algorithm.By setting the different numbers of AGVs(Automated Guided Vehicles)and analyzing the impact on the production cycle of the whole order,this paper uses two indicators,the maximum completion time decreasing rate and the average AGV load time,to obtain the optimal number of AGVs,which saves the cost of production while ensuring the production efficiency.This research combines the solved problem with the real production process,which improves the productivity and reduces the production cost of the flexible job shop,and provides new ideas for the subsequent research.展开更多
间歇生产过程具有弹性大、灵活等特点,其市场适应性较强。化工生产中间歇生产过程占相当比例,文章就间歇生产工艺的模拟与优化进行介绍,利用Aspen Batch Process Developer模拟间歇工艺过程,可以快速地得到工艺流程的物料衡算、热量衡...间歇生产过程具有弹性大、灵活等特点,其市场适应性较强。化工生产中间歇生产过程占相当比例,文章就间歇生产工艺的模拟与优化进行介绍,利用Aspen Batch Process Developer模拟间歇工艺过程,可以快速地得到工艺流程的物料衡算、热量衡算、操作时间、公用工程和成本估算等结果。同时,还可以对模拟结果进行分析,找出制约生产工艺的瓶颈,并对生产周期、生产规模、生产设备等进行优化,提高工艺设计效率,降低生产成本。展开更多
基金Supported by the National Natural Science Foundation of China （20536020, 20876056）.
文摘Chemical batch processes have become significant in chemical manufacturing. In these processes, large numbers of chemical products are produced to satisfy human demands in daily life. Recently, economy globalization has resulted, in growing worldwide competitions in tradi.tional chemical .process industry. In order to keep competitive in the global marketplace, each company must optimize its production management and set up a reactive system for market fluctuation. Scheduling is the core of production management in chemical processes. The goal of this paper is to review the recent developments in this challenging area. Classifications of batch scheduling problems and optimization methods are introduced. A comparison of six typical models is shown in a general benchmark example from the literature. Finally, challenges and applications in future research are discussed.
文摘It is the fact that several process parameters are either unknown or uncertain. Therefore, an optimal control, profile calculated with developed process models with respect to such process parameters may not give an optimal performance when implemented to real processes. This study proposes a batch-to-batch optimization strategy for the estimation of uncertain kinetic.par.ameters in a batch crystallization process of potassium sulfate production. The knowledge of a crystal size distribution of the product at the end of batch operation is used in the proposed methodology. The updated kinetic parameters are applied for determining an optimal operating temperature policy for the next batch run.
基金supported by the National Key R&D Plan(2020YFB1712902)the National Natural Science Foundation of China(52075036).
文摘In order to solve the flexible job shop scheduling problem with variable batches,we propose an improved multiobjective optimization algorithm,which combines the idea of inverse scheduling.First,a flexible job shop problem with the variable batches scheduling model is formulated.Second,we propose a batch optimization algorithm with inverse scheduling in which the batch size is adjusted by the dynamic feedback batch adjusting method.Moreover,in order to increase the diversity of the population,two methods are developed.One is the threshold to control the neighborhood updating,and the other is the dynamic clustering algorithm to update the population.Finally,a group of experiments are carried out.The results show that the improved multi-objective optimization algorithm can ensure the diversity of Pareto solutions effectively,and has effective performance in solving the flexible job shop scheduling problem with variable batches.
文摘An efficient culture medium producing a bacterial elastase with high yields was developed further following preliminary studies by means of response surface method. Central composite design (CCD) and response surface method-ology were applied to optimize the medium constituents. A central composite design was used to explain the combined effect of three medium constituents, viz, glucose, K2HPO4, MgSO47H2O. The strain produced more elastase in the completely optimized medium, as compared with the partially optimized medium. The fitted model of the second model, as per RSM, showed that glucose was 7.4 g/100 ml, casein 1.13 g/100 ml, corn steep flour 0.616 g/100 ml, K2HPO4 0.206 g/100 ml and MgSO47H2O 0.034 g/100 ml. The fermentation kinetics of these two culture media in the flask experiments were analyzed. It was found that the highest elastase productivity occurred at 54 hours. Higher glucose concentration had inhibitory effect on elastase production. At the same time, we observed that the glucose consumption rate was slow in the completely optimized medium, which can explain the lag period of the highest elastase production. Some metal ions and surfactant additives also affected elastase production and cell growth.
基金National Natural Science Foundation of China(No.60504033)
文摘An iterative (run-to-run) optimization method was presented for batch processes under input constraints. Generally it is very difficult to acquire an accurate mechanistic model for a batch process.Because support vector machine is powerful for the problems characterized by small samples,nonlinearity, high dimension and local minima, support vector regression models were developed for the end-point optimization of batch processes. Since there is no analytical way to find the optimal trajectory, an iterative method was used to exploit the repetitive nature of batch processes to determine the optimal operating policy. The optimization algorithm is proved convergent. The numerical simulation shows that the method can improve the process performance through iterations.
文摘Batch distillation,basically different from continuous distillation which is a steady stateprocess,appears to be an unsteady state process in its mathematical description.The theoreticalanalysis of its operation comprises a concomitant consideration of the stage-wise separation andthe equations of material balance as well as enthalpy balance.Based upon the batch distillationpractice of NMP-water system,this paper reveals the necessity and advantage of a computerizedtreatment for this purpose.Numerical results not only explain the experimental phenomena andprovide a design scheme,but also lead to the optimization of the operation condition.
文摘With the rapid development of intelligent manufacturing and the changes in market demand,the current manufacturing industry presents the characteristics of multi-varieties,small batches,customization,and a short production cycle,with the whole production process having certain flexibility.In this paper,a mathematical model is established with the minimum production cycle as the optimization objective for the dual-resource batch scheduling of the flexible job shop,and an improved nested optimization algorithm is designed to solve the problem.The outer layer batch optimization problem is solved by the improved simulated annealing algorithm.The inner double resource scheduling problem is solved by the improved adaptive genetic algorithm,the double coding scheme,and the decoding scheme of Automated Guided Vehicle(AGV)scheduling based on the scheduling rules.The time consumption of collision-free paths is solved with the path planning algorithm which uses the Dijkstra algorithm based on a time window.Finally,the effectiveness of the algorithm is verified by actual cases,and the influence of AGV with different configurations on workshop production efficiency is analyzed.
文摘This paper employs mathematical modeling and algebraic approach to derive the optimal manufacturing batch size and number of shipment for a vendor-buyer integrated economic production quantity (EPQ) model with scrap. Unlike the conventional method by using differential calculus to determine replenishment lot size and optimal number of shipments for such an integrated system, this paper proposes a straightforward algebraic approach to replace the use of calculus on the total cost function for solving the optimal production- shipment policies. A simpler form for computing long-run average cost for such a vendor- buyer integrated EPQ problem is also provided.
基金This work was supported by the UK EPSRC (GR/N13319, GR/R10875).
文摘In this paper, the modelling and multi-objective optimal control of batch processes, using a recurrent neuro-fuzzy network, are presented. The recurrent neuro-fuzzy network, forms a ＂global＂ nonlinear long-range prediction model through the fuzzy conjunction of a number of ＂local＂ linear dynamic models. Network output is fed back to network input through one or more time delay units, which ensure that predictions from the recurrent neuro-fuzzy network are long-range. In building a recurrent neural network model, process knowledge is used initially to partition the processes non-linear characteristics into several local operating regions, and to aid in the initialisation of corresponding network weights. Process operational data is then used to train the network. Membership functions of the local regimes are identified, and local models are discovered via network training. Based on a recurrent neuro-fuzzy network model, a multi-objective optimal control policy can be obtained. The proposed technique is applied to a fed-batch reactor.
基金Supported by UK EPSRC (grants GR/N13319 and GR/R 10875)
文摘This paper presents several neural network based modelling, reliable optimal control, and iterative learning control methods for batch processes. In order to overcome the lack of robustness of a single neural network, bootstrap aggregated neural networks are used to build reliable data based empirical models. Apart from improving the model generalisation capability, a bootstrap aggregated neural network can also provide model prediction confidence bounds. A reliable optimal control method by incorporating model prediction confidence bounds into the optimisation objective function is presented. A neural network based iterative learning control strategy is presented to overcome the problem due to unknown disturbances and model-plant mismatches. The proposed methods are demonstrated on a simulated batch polymerisation process.
基金Supported by the National Natural Science Foundation of China,No.29476248 and Trans-Century Training Program Foundation for the Talents by the State Education Commission.
文摘In this paper,a novel fuzzy neural network model,in which an adjustable fuzzy sub-space was designed by uniform design,has been established and used in fed-batch yeast fermentationas an example.A brand-new optimization sub-network with special structure has been built andgenetic algorithm,guaranteeing the optimization in overall space,is introduced for the feed rateoptimization.On the basis of the model network,the optimal substrate concentration and theoptimal amount of fed-batch at different periods have been studied,aided with the optimizationnetwork and the genetic algorithm separately.The above results can be used as a basis for theestablishment of a fuzzy neural network controller.
文摘To improve the productivity,the resource utilization and reduce the production cost of flexible job shops,this paper designs an improved two-layer optimization algorithm for the dual-resource scheduling optimization problem of flexible job shop considering workpiece batching.Firstly,a mathematical model is established to minimize the maximum completion time.Secondly,an improved two-layer optimization algorithm is designed:the outer layer algorithm uses an improved PSO(Particle Swarm Optimization)to solve the workpiece batching problem,and the inner layer algorithm uses an improved GA(Genetic Algorithm)to solve the dual-resource scheduling problem.Then,a rescheduling method is designed to solve the task disturbance problem,represented by machine failures,occurring in the workshop production process.Finally,the superiority and effectiveness of the improved two-layer optimization algorithm are verified by two typical cases.The case results show that the improved two-layer optimization algorithm increases the average productivity by 7.44% compared to the ordinary two-layer optimization algorithm.By setting the different numbers of AGVs(Automated Guided Vehicles)and analyzing the impact on the production cycle of the whole order,this paper uses two indicators,the maximum completion time decreasing rate and the average AGV load time,to obtain the optimal number of AGVs,which saves the cost of production while ensuring the production efficiency.This research combines the solved problem with the real production process,which improves the productivity and reduces the production cost of the flexible job shop,and provides new ideas for the subsequent research.
文摘间歇生产过程具有弹性大、灵活等特点,其市场适应性较强。化工生产中间歇生产过程占相当比例,文章就间歇生产工艺的模拟与优化进行介绍,利用Aspen Batch Process Developer模拟间歇工艺过程,可以快速地得到工艺流程的物料衡算、热量衡算、操作时间、公用工程和成本估算等结果。同时,还可以对模拟结果进行分析,找出制约生产工艺的瓶颈,并对生产周期、生产规模、生产设备等进行优化,提高工艺设计效率,降低生产成本。
