In the present work, two new, （multi-）parametric programming （mp-P）-inspired algorithms for the solutionof mixed-integer nonlinear programming （MINLP） problems are developed, with their main focus being onproces...In the present work, two new, （multi-）parametric programming （mp-P）-inspired algorithms for the solutionof mixed-integer nonlinear programming （MINLP） problems are developed, with their main focus being onprocess synthesis problems. The algorithms are developed for the special case in which the nonlinearitiesarise because of logarithmic terms, with the first one being developed for the deterministic case, and thesecond for the parametric case （p-MINLP）. The key idea is to formulate and solve the square system of thefirst-order Karush-Kuhn-Tucker （KKT） conditions in an analytical way, by treating the binary variables and/or uncertain parameters as symbolic parameters. To this effect, symbolic manipulation and solution tech-niques are employed. In order to demonstrate the applicability and validity of the proposed algorithms, twoprocess synthesis case studies are examined. The corresponding solutions are then validated using state-of-the-art numerical MINLP solvers. For p-MINLP, the solution is given by an optimal solution as an explicitfunction of the uncertain parameters.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
The models, algorithms and implementation results of a computerized scheduling system were introduced for the steelmaking-continuous casting process （SCCP） of a steel plant in China. The scheduling of SCCP in this p...The models, algorithms and implementation results of a computerized scheduling system were introduced for the steelmaking-continuous casting process （SCCP） of a steel plant in China. The scheduling of SCCP in this plant required that each cast plan should be processed on time, the charges in the same cast should be processed con- tinuously on the same caster, and the waiting time of the charges which are in front of each caster cannot exceed the given threshold. At the same time, the processing time of charges cannot be conflicted mutually in the same convert- ers or refining furnaces. Based on the research background, a hybrid optimal scheduling approach and its application were discussed. Aiming at the main equipment scheduling, an optimal scheduling method was proposed which con- sisted of equipment assignment algorithm based on dynamic program （DP） technique and conflict elimination algo rithm based on linear program （LP） technique. The approach guarantees that the charges are continuously processed on the same caster. Meanwhile, the requirement for high temperature ladle can also be satisfied due to the ladle matching function. Numerical results demonstrate solution quality, computational efficiency, and values of the mod els and algorithm.展开更多
An alpha-uniformized Markov chain is defined by the concept of equivalent infinitesimalgenerator for a semi-Markov decision process (SMDP) with both average- and discounted-criteria.According to the relations of their...An alpha-uniformized Markov chain is defined by the concept of equivalent infinitesimalgenerator for a semi-Markov decision process (SMDP) with both average- and discounted-criteria.According to the relations of their performance measures and performance potentials, the optimiza-tion of an SMDP can be realized by simulating the chain. For the critic model of neuro-dynamicprogramming (NDP), a neuro-policy iteration (NPI) algorithm is presented, and the performanceerror bound is shown as there are approximate error and improvement error in each iteration step.The obtained results may be extended to Markov systems, and have much applicability. Finally, anumerical example is provided.展开更多
A neruon-oriented programming system based on parallel neural information processing has been presented. With the neural programming system built upon 4～8 process elements(TMS C30), the system has thus provided users...A neruon-oriented programming system based on parallel neural information processing has been presented. With the neural programming system built upon 4～8 process elements(TMS C30), the system has thus provided users high speed, general purpose and large scale neural network application development platforms etc.展开更多
Markov decision processes （MDPs） and their variants are widely studied in the theory of controls for stochastic discrete- event systems driven by Markov chains. Much of the literature focusses on the risk-neutral cr...Markov decision processes （MDPs） and their variants are widely studied in the theory of controls for stochastic discrete- event systems driven by Markov chains. Much of the literature focusses on the risk-neutral criterion in which the expected rewards, either average or discounted, are maximized. There exists some literature on MDPs that takes risks into account. Much of this addresses the exponential utility （EU） function and mechanisms to penalize different forms of variance of the rewards. EU functions have some numerical deficiencies, while variance measures variability both above and below the mean rewards; the variability above mean rewards is usually beneficial and should not be penalized/avoided. As such, risk metrics that account for pre-specified targets （thresholds） for rewards have been considered in the literature, where the goal is to penalize the risks of revenues falling below those targets. Existing work on MDPs that takes targets into account seeks to minimize risks of this nature. Minimizing risks can lead to poor solutions where the risk is zero or near zero, but the average rewards are also rather low. In this paper, hence, we study a risk-averse criterion, in particular the so-called downside risk, which equals the probability of the revenues falling below a given target, where, in contrast to minimizing such risks, we only reduce this risk at the cost of slightly lowered average rewards. A solution where the risk is low and the average reward is quite high, although not at its maximum attainable value, is very attractive in practice. To be more specific, in our formulation, the objective function is the expected value of the rewards minus a scalar times the downside risk. In this setting, we analyze the infinite horizon MDP, the finite horizon MDP, and the infinite horizon semi-MDP （SMDP）. We develop dynamic programming and reinforcement learning algorithms for the finite and infinite horizon. The algorithms are tested in numerical studies and show encouraging performance.展开更多
CN-85 detector which covered with boric acid H3Bo3 pellete has been irradiated by thermal neutrons from (241Am-9Be) source with activity 12 Ci and neutron flux 105 n. cm-2. s-1. The irradiation times-TD for detector w...CN-85 detector which covered with boric acid H3Bo3 pellete has been irradiated by thermal neutrons from (241Am-9Be) source with activity 12 Ci and neutron flux 105 n. cm-2. s-1. The irradiation times-TD for detector were 4 h, 8 h, 16 h and 24 h. The track detector has been etched with sodium hydroxide. After chemical etching of the irradiated CN-85 detector, the images have been taken from a digital camera connected to the optical microscope. Image processing for the output images has been performed using MATALB program, and these images were analyzed and we had found the following relations: a) The relation between summation of opened track or surface density for tracks (intensity-IT) varies with radius of opening (track radius-RT). b) The relation between the tracks number-NT varies with the tracks diameter-DT (in micrometer) and tracks area-AT. That analysis of image processing was obtained, and the track intensity-IT was decreased with increase of track radius-RT at all of the irradiation time-TD. And the track intensity-IT was increased with increasing irradiation time-TD (h) for different track radius-RT (0.4225, 0.845, 1.2675 and 1.69 μm). The study indicates the possibility of using the analysis of image processing to CN-85 detector for classification of α-particle emitters through limitation of radius of track-RT, in addition to the contribution of these techniques in preparation of nano-filters and nono-membrane in nanotechnology fields.展开更多
In order to enhance the NC programming efficiency and quality of aircraft structural parts （ASPs）, an intelligent NC programming pattern driven by process schemes is presented. In this pattern, the NC machining cell...In order to enhance the NC programming efficiency and quality of aircraft structural parts （ASPs）, an intelligent NC programming pattern driven by process schemes is presented. In this pattern, the NC machining cell is the minimal organizational structure in the technological process, consisting of an operation machining volume cell, and the type and parameters of the machining operation. After the machining cell construction, the final NC program can be easily obtained in a CAD/CAM system by instantiating the machining operation for each machining cell. Accordingly, how to automatically establish the machining cells is a key issue in intelligent NC program- ming. On the basis of the NC machining craft of ASP, the paper aims to make an in-depth research on this issue. Firstly, some new terms about the residual volume and the machinable volume are defined, and then, the technological process is modeled with a process scheme. Secondly, the approach to building the machining cells is introduced, in which real-time complement machining is mainly considered to avoid interference and overcutting. Thirdly, the implementing algorithm is designed and applied to the Intelligent NC Programming System of ASP. Finally, the developed algorithm is validated through two case studies.展开更多
Control of the fed-batch ethanol fermentation processes to produce maximum product ethanol is one of the key issues in the bioreactor system.However,ethanol fermentation processes exhibit complex behavior and nonlinea...Control of the fed-batch ethanol fermentation processes to produce maximum product ethanol is one of the key issues in the bioreactor system.However,ethanol fermentation processes exhibit complex behavior and nonlinear dynamics with respect to the cell mass,substrate,feed-rate,etc.An improved dual heuristic programming algorithm based on the least squares temporal difference with gradient correction(LSTDC) algorithm(LSTDC-DHP) is proposed to solve the learning control problem of a fed-batch ethanol fermentation process.As a new algorithm of adaptive critic designs,LSTDC-DHP is used to realize online learning control of chemical dynamical plants,where LSTDC is commonly employed to approximate the value functions.Application of the LSTDC-DHP algorithm to ethanol fermentation process can realize efficient online learning control in continuous spaces.Simulation results demonstrate the effectiveness of LSTDC-DHP,and show that LSTDC-DHP can obtain the near-optimal feed rate trajectory faster than other-based algorithms.展开更多
In recent years, the widespread adoption of parallel computing, especially in multi-core processors and high-performance computing environments, ushered in a new era of efficiency and speed. This trend was particularl...In recent years, the widespread adoption of parallel computing, especially in multi-core processors and high-performance computing environments, ushered in a new era of efficiency and speed. This trend was particularly noteworthy in the field of image processing, which witnessed significant advancements. This parallel computing project explored the field of parallel image processing, with a focus on the grayscale conversion of colorful images. Our approach involved integrating OpenMP into our framework for parallelization to execute a critical image processing task: grayscale conversion. By using OpenMP, we strategically enhanced the overall performance of the conversion process by distributing the workload across multiple threads. The primary objectives of our project revolved around optimizing computation time and improving overall efficiency, particularly in the task of grayscale conversion of colorful images. Utilizing OpenMP for concurrent processing across multiple cores significantly reduced execution times through the effective distribution of tasks among these cores. The speedup values for various image sizes highlighted the efficacy of parallel processing, especially for large images. However, a detailed examination revealed a potential decline in parallelization efficiency with an increasing number of cores. This underscored the importance of a carefully optimized parallelization strategy, considering factors like load balancing and minimizing communication overhead. Despite challenges, the overall scalability and efficiency achieved with parallel image processing underscored OpenMP’s effectiveness in accelerating image manipulation tasks.展开更多
基金financial support from EPSRC grants (EP/M027856/1 EP/M028240/1)
文摘In the present work, two new, （multi-）parametric programming （mp-P）-inspired algorithms for the solutionof mixed-integer nonlinear programming （MINLP） problems are developed, with their main focus being onprocess synthesis problems. The algorithms are developed for the special case in which the nonlinearitiesarise because of logarithmic terms, with the first one being developed for the deterministic case, and thesecond for the parametric case （p-MINLP）. The key idea is to formulate and solve the square system of thefirst-order Karush-Kuhn-Tucker （KKT） conditions in an analytical way, by treating the binary variables and/or uncertain parameters as symbolic parameters. To this effect, symbolic manipulation and solution tech-niques are employed. In order to demonstrate the applicability and validity of the proposed algorithms, twoprocess synthesis case studies are examined. The corresponding solutions are then validated using state-of-the-art numerical MINLP solvers. For p-MINLP, the solution is given by an optimal solution as an explicitfunction of the uncertain parameters.
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Item Sponsored by National Natural Science Foundation of China(61174187,71021061,60974091,61104174)Startup Fund of Northeastern University of China(29321006)Basic Scientific Research Foundation of Northeast University of China(N110208001)
文摘The models, algorithms and implementation results of a computerized scheduling system were introduced for the steelmaking-continuous casting process （SCCP） of a steel plant in China. The scheduling of SCCP in this plant required that each cast plan should be processed on time, the charges in the same cast should be processed con- tinuously on the same caster, and the waiting time of the charges which are in front of each caster cannot exceed the given threshold. At the same time, the processing time of charges cannot be conflicted mutually in the same convert- ers or refining furnaces. Based on the research background, a hybrid optimal scheduling approach and its application were discussed. Aiming at the main equipment scheduling, an optimal scheduling method was proposed which con- sisted of equipment assignment algorithm based on dynamic program （DP） technique and conflict elimination algo rithm based on linear program （LP） technique. The approach guarantees that the charges are continuously processed on the same caster. Meanwhile, the requirement for high temperature ladle can also be satisfied due to the ladle matching function. Numerical results demonstrate solution quality, computational efficiency, and values of the mod els and algorithm.
文摘An alpha-uniformized Markov chain is defined by the concept of equivalent infinitesimalgenerator for a semi-Markov decision process (SMDP) with both average- and discounted-criteria.According to the relations of their performance measures and performance potentials, the optimiza-tion of an SMDP can be realized by simulating the chain. For the critic model of neuro-dynamicprogramming (NDP), a neuro-policy iteration (NPI) algorithm is presented, and the performanceerror bound is shown as there are approximate error and improvement error in each iteration step.The obtained results may be extended to Markov systems, and have much applicability. Finally, anumerical example is provided.
文摘A neruon-oriented programming system based on parallel neural information processing has been presented. With the neural programming system built upon 4～8 process elements(TMS C30), the system has thus provided users high speed, general purpose and large scale neural network application development platforms etc.
文摘Markov decision processes （MDPs） and their variants are widely studied in the theory of controls for stochastic discrete- event systems driven by Markov chains. Much of the literature focusses on the risk-neutral criterion in which the expected rewards, either average or discounted, are maximized. There exists some literature on MDPs that takes risks into account. Much of this addresses the exponential utility （EU） function and mechanisms to penalize different forms of variance of the rewards. EU functions have some numerical deficiencies, while variance measures variability both above and below the mean rewards; the variability above mean rewards is usually beneficial and should not be penalized/avoided. As such, risk metrics that account for pre-specified targets （thresholds） for rewards have been considered in the literature, where the goal is to penalize the risks of revenues falling below those targets. Existing work on MDPs that takes targets into account seeks to minimize risks of this nature. Minimizing risks can lead to poor solutions where the risk is zero or near zero, but the average rewards are also rather low. In this paper, hence, we study a risk-averse criterion, in particular the so-called downside risk, which equals the probability of the revenues falling below a given target, where, in contrast to minimizing such risks, we only reduce this risk at the cost of slightly lowered average rewards. A solution where the risk is low and the average reward is quite high, although not at its maximum attainable value, is very attractive in practice. To be more specific, in our formulation, the objective function is the expected value of the rewards minus a scalar times the downside risk. In this setting, we analyze the infinite horizon MDP, the finite horizon MDP, and the infinite horizon semi-MDP （SMDP）. We develop dynamic programming and reinforcement learning algorithms for the finite and infinite horizon. The algorithms are tested in numerical studies and show encouraging performance.
文摘CN-85 detector which covered with boric acid H3Bo3 pellete has been irradiated by thermal neutrons from (241Am-9Be) source with activity 12 Ci and neutron flux 105 n. cm-2. s-1. The irradiation times-TD for detector were 4 h, 8 h, 16 h and 24 h. The track detector has been etched with sodium hydroxide. After chemical etching of the irradiated CN-85 detector, the images have been taken from a digital camera connected to the optical microscope. Image processing for the output images has been performed using MATALB program, and these images were analyzed and we had found the following relations: a) The relation between summation of opened track or surface density for tracks (intensity-IT) varies with radius of opening (track radius-RT). b) The relation between the tracks number-NT varies with the tracks diameter-DT (in micrometer) and tracks area-AT. That analysis of image processing was obtained, and the track intensity-IT was decreased with increase of track radius-RT at all of the irradiation time-TD. And the track intensity-IT was increased with increasing irradiation time-TD (h) for different track radius-RT (0.4225, 0.845, 1.2675 and 1.69 μm). The study indicates the possibility of using the analysis of image processing to CN-85 detector for classification of α-particle emitters through limitation of radius of track-RT, in addition to the contribution of these techniques in preparation of nano-filters and nono-membrane in nanotechnology fields.
基金supported by National Science and Technology Major Project (No.2012ZX04010051)
文摘In order to enhance the NC programming efficiency and quality of aircraft structural parts （ASPs）, an intelligent NC programming pattern driven by process schemes is presented. In this pattern, the NC machining cell is the minimal organizational structure in the technological process, consisting of an operation machining volume cell, and the type and parameters of the machining operation. After the machining cell construction, the final NC program can be easily obtained in a CAD/CAM system by instantiating the machining operation for each machining cell. Accordingly, how to automatically establish the machining cells is a key issue in intelligent NC program- ming. On the basis of the NC machining craft of ASP, the paper aims to make an in-depth research on this issue. Firstly, some new terms about the residual volume and the machinable volume are defined, and then, the technological process is modeled with a process scheme. Secondly, the approach to building the machining cells is introduced, in which real-time complement machining is mainly considered to avoid interference and overcutting. Thirdly, the implementing algorithm is designed and applied to the Intelligent NC Programming System of ASP. Finally, the developed algorithm is validated through two case studies.
基金Supported by the National Natural Science Foundation of China(61573052)
文摘Control of the fed-batch ethanol fermentation processes to produce maximum product ethanol is one of the key issues in the bioreactor system.However,ethanol fermentation processes exhibit complex behavior and nonlinear dynamics with respect to the cell mass,substrate,feed-rate,etc.An improved dual heuristic programming algorithm based on the least squares temporal difference with gradient correction(LSTDC) algorithm(LSTDC-DHP) is proposed to solve the learning control problem of a fed-batch ethanol fermentation process.As a new algorithm of adaptive critic designs,LSTDC-DHP is used to realize online learning control of chemical dynamical plants,where LSTDC is commonly employed to approximate the value functions.Application of the LSTDC-DHP algorithm to ethanol fermentation process can realize efficient online learning control in continuous spaces.Simulation results demonstrate the effectiveness of LSTDC-DHP,and show that LSTDC-DHP can obtain the near-optimal feed rate trajectory faster than other-based algorithms.
文摘In recent years, the widespread adoption of parallel computing, especially in multi-core processors and high-performance computing environments, ushered in a new era of efficiency and speed. This trend was particularly noteworthy in the field of image processing, which witnessed significant advancements. This parallel computing project explored the field of parallel image processing, with a focus on the grayscale conversion of colorful images. Our approach involved integrating OpenMP into our framework for parallelization to execute a critical image processing task: grayscale conversion. By using OpenMP, we strategically enhanced the overall performance of the conversion process by distributing the workload across multiple threads. The primary objectives of our project revolved around optimizing computation time and improving overall efficiency, particularly in the task of grayscale conversion of colorful images. Utilizing OpenMP for concurrent processing across multiple cores significantly reduced execution times through the effective distribution of tasks among these cores. The speedup values for various image sizes highlighted the efficacy of parallel processing, especially for large images. However, a detailed examination revealed a potential decline in parallelization efficiency with an increasing number of cores. This underscored the importance of a carefully optimized parallelization strategy, considering factors like load balancing and minimizing communication overhead. Despite challenges, the overall scalability and efficiency achieved with parallel image processing underscored OpenMP’s effectiveness in accelerating image manipulation tasks.
