In this paper, we study a class of manufacturing systems which consist of multiple plants and each of the plants has capability of producing multiple distinct products. The production lines of a certain plant may swit...In this paper, we study a class of manufacturing systems which consist of multiple plants and each of the plants has capability of producing multiple distinct products. The production lines of a certain plant may switch between producing different kinds of products in a time-sharing mode. We optimize the capacity configuration of such a system s production lines with the objective to maximize the overall profit in the capacity planning horizon. Uncertain demand is incorporated in the model to achieve a robust configuration solution. The optimization problem is formulated as a nonlinear polynomial stochastic programming problem, which is difficult to be efficiently solved due to demand uncertainties and large search space. We show the NP-hardness of the problem first, and then apply ordinal optimization(OO) method to search for good enough designs with high probability. At lower level, an mixed integer programming(MIP) solving tool is employed to evaluate the performance of a design under given demand profile.展开更多
The Fork-Join program consisting of K parallel tasks is a useful model for a large number of computing applications. When the parallel processor has multi-channels, later tasks may finish execution earlier than their ...The Fork-Join program consisting of K parallel tasks is a useful model for a large number of computing applications. When the parallel processor has multi-channels, later tasks may finish execution earlier than their earlier tasks and may join with tasks from other programs. This phenomenon is called exchangeable join (EJ), which introduces correlation to the task’s service time. In this work, we investigate the response time of multiprocessor systems with EJ with a new approach. We analyze two aspects of this kind of systems: exchangeable join (EJ) and the capacity constraint (CC). We prove that the system response time can be effectively reduced by EJ, while the reduced amount is constrained by the capacity of the multiprocessor. An upper bound model is constructed based on this analysis and a quick estimation algorithm is proposed. The approximation formula is verified by extensive simulation results, which show that the relative error of approximation is less than 5%.展开更多
The evaluation system is significant for assessment of technologies, experiments, energy cost and effectiveness, especially for the complicated engineering systems, such as energy systems, weapon systems and spacecraf...The evaluation system is significant for assessment of technologies, experiments, energy cost and effectiveness, especially for the complicated engineering systems, such as energy systems, weapon systems and spacecraft systems. However, as engineering systems become more and more distributed and heterogeneous, evaluation frameworks need to be more universal,distributed and interactive. In this paper, we compare several typical evaluation frameworks and propose a novel evaluation framework based on multi-agent technology. We provide two case studies, indoor comfort system and technology assessment of spacecraft systems, respectively. The results show that the proposed framework can work efficiently.展开更多
Operation scheduling for a class of production systems with"instantly consumed"products is very important.It is challenging to satisfy the real time system demand and to consider the realizability of the pro...Operation scheduling for a class of production systems with"instantly consumed"products is very important.It is challenging to satisfy the real time system demand and to consider the realizability of the production schedules.This paper formulates a new model for optimization based production scheduling problems with integral constraints.Based on the detailed analysis of the production rate constraints,it is proved that this type of optimization problems is equivalent to a smooth nonlinear programming problem.The reachable upper and lower bounds of the production amount in every period can be expressed as functions of two variables,i.e.,the production rate at the start and end of that period.It is also proved that the gradients of these functions are monotonic,and their convexity or concavity is guaranteed.When the production cost function is convex,this type of optimization problems is equivalent to a convex programming problem.With the above analysis,a two-stage solution method is developed to solve the production scheduling problems with integral constraints,and in many applications the global optimal solution can be obtained efficiently.With the new model and solution method,the difficulties caused by the constraints on production rate can be overcome and the optimal schedule can be obtained with the real time system demand satisfied.Numerical testing for scheduling of electric power production systems is performed and the testing results are discussed.It is demonstrated that the new model and solution method are effective.展开更多
Buildings worldwide account for nearly 40%of global energy consumption.The biggest energy consumer in buildings is the heating,ventilation and air conditioning(HVAC)systems.In HVAC systems,chillers account for a major...Buildings worldwide account for nearly 40%of global energy consumption.The biggest energy consumer in buildings is the heating,ventilation and air conditioning(HVAC)systems.In HVAC systems,chillers account for a major portion of the energy consumption.Maintaining chillers in good conditions through early fault detection and diagnosis is thus a critical issue.In this paper,the fault detection and diagnosis for an air-cooled chiller with air coming from outside in variable flow rates is studied.The problem is difficult since the air-cooled chiller is operating under major uncertainties including the cooling load,and the air temperature and flow rate.A potential method to overcome the difficulty caused by the uncertainties is to perform fault detection and diagnosis based on a gray-box model with parameters regarded as constants.The method is developed and verified by us in another paper for a water-cooled chiller with the uncertainty of cooling load.The verification used a Kalman filter to predict parameters of a gray-box model and statistical process control(SPC)for measuring and analyzing their variations for fault detection and diagnosis.The gray-box model in the method,however,requires that the air temperature and flow rate be nearly constant.By introducing two new parameters and deleting data points with low air flow rate,the requirement can be satisfied and the method can then be applicable for an air-cooled chiller.The simulation results show that the method with the revised model and some data points dropped improved the fault detection and diagnosis(FDD)performance greatly.It can detect both sudden and gradual air-cooled chiller capacity degradation and sensor faults as well as their recoveries.展开更多
The influence of a node in a network can be characterized by its macroscopic properties such as eigenvector centrality. An issue of significant theoretical and practical interest is to modify the influence or roles of...The influence of a node in a network can be characterized by its macroscopic properties such as eigenvector centrality. An issue of significant theoretical and practical interest is to modify the influence or roles of the nodes in a network, and recent advances indicate that this can be achieved by just controlling a subset of nodes: the socalled controllers. However, the relationship between the structural properties of a network and its controllability, e.g., the control of node importance, is still not well understood. Here we systematically" explore this relationship by constructing scale-free networks with a fixed degree sequence and tunable network characteristics. We calculate the relative size (nc*) of the minimai controlling set required to controi the importance of each individual node in a network. It is found that while clustering has no significant impact on nc*, changes in degree-degree correlations, heterogeneity and the average degree of networks demonstrate a discernible impact on its controllability.展开更多
The adoption and usage of electric vehicles(EVs)have emerged recently due to the increasing concerns on the greenhouse gas issues and energy revolution.As a part of the smart grid,EVs can provide valuable ancillary se...The adoption and usage of electric vehicles(EVs)have emerged recently due to the increasing concerns on the greenhouse gas issues and energy revolution.As a part of the smart grid,EVs can provide valuable ancillary services beyond consumers of electricity.However,EVs are gradually considered as nonnegligible loads due to their increasing penetration,which may result in negative effects such as voltage deviations,lines saturation,and power losses.Relationship and interaction among EVs,charging stations,and micro grid have to be considered in the next generation of smart grid.Therefore,the topic of smart charging has been the focus of many works where a wide range of control methods have been developed.As one of the bases of simulation,the EV charging behavior and characteristics have also become the focus of many studies.In this work,we review the charging behavior of EVs from the aspects of data,model,and control.We provide the links for most of the data sets reviewed in this work,based on which interested researchers can easily access these data for further investigation.展开更多
Fire detection in buildings is crucial for people’s lives and property.Conventional temperature and smoke sen-sors have many disadvantages:the limited cover range;detection delays;the difficulty in distinguishing smo...Fire detection in buildings is crucial for people’s lives and property.Conventional temperature and smoke sen-sors have many disadvantages:the limited cover range;detection delays;the difficulty in distinguishing smoke and fire.Recently,research on convolutional neural networks(CNN)for fire image detection has become a hot topic.However,existing fire classification and object detection methods are often interfered with by flash-lights,red objects and the high-brightness background,resulting in a high false alarm rate.Besides,light and lamps often exist in buildings.To address this issue,this paper focuses on introducing scene prior knowledge and causal inference mechanisms to suppress the lamp disturbance.Firstly,we train the YoloV3 network to detect and recognize lamps.Secondly,to reduce the dataset bias,we mask the lamp regions with the pro-posed Local Grabcut segmentation method.Last,compared with direct fire classification methods,our proposed methods reduce about 34.6%false alarm rate based on InceptionV4 networks.The experimental results verify the effectiveness among different CNN architectures(Resnet101,Firenet,Densenet121).The code is online at https://github.com/kailaisun/fire-detection-without-lamp.展开更多
The matching between dynamic supply of renewable power generation and flexible charging demand ofthe Electric Vehicles (EVs) can not only increase the penetration of renewables but also reduce the load to the stateele...The matching between dynamic supply of renewable power generation and flexible charging demand ofthe Electric Vehicles (EVs) can not only increase the penetration of renewables but also reduce the load to the stateelectric power grid. The challenges herein are the curse of dimensionality, the multiple decision making stagesinvolved, and the uncertainty of both the supply and demand sides. Event-Based Optimization (EBO) provides a newway to solve large-scale Markov decision process. Considering different spatial scales, we develop a bi-level EBOmodel in this paper which can both catch the changes on the macro and micro levels. By proper definition, the sizeof event space stays fixed with the scale of the problem, which shows good scalability in online optimization. Then abi-level Q-learning method is developed to solve the problem iteratively. We demonstrate the performance of themethod by numerical examples. Our method outperforms other methods both in performance and scalability.展开更多
The optimal control of a Markov jump linear quadratic model with controlled jump probabilities of modes is investigated.Two kinds of mode control policies,i.e.,open-loop control policy and closed-loop control policy,a...The optimal control of a Markov jump linear quadratic model with controlled jump probabilities of modes is investigated.Two kinds of mode control policies,i.e.,open-loop control policy and closed-loop control policy,are considered.Using the concepts of policy iteration and performance potential,the sufficient condition needed for the optimal closed-loop control policy to perform better than the optimal open-loop control policy is proposed.The condition is helpful for the design of an optimal controller.Furthermore,an efficient algorithm to construct a closed-loop control policy,which is better than the optimal open-loop control policy,is given with policy iteration.展开更多
If the decade of 1990s were the period of Globalization,the first ten years of this new century can certainly be characterized as the age of Connectedness.Through“connectedness”the world becomes Friedmanianly flat,p...If the decade of 1990s were the period of Globalization,the first ten years of this new century can certainly be characterized as the age of Connectedness.Through“connectedness”the world becomes Friedmanianly flat,people are enabled,informed,and equipped to deal with a complex,hot,and crowded world.Not only there is the ubiquitous Internet from which all of us are increasingly dependent,but there are many other kinds of networks,social,commercial,economic,and military that drive our civilization.展开更多
SQL injection poses a major threat to the application level security of the database and there is no systematic solution to these attacks.Different from traditional run time security strategies such as IDS and fire-wa...SQL injection poses a major threat to the application level security of the database and there is no systematic solution to these attacks.Different from traditional run time security strategies such as IDS and fire-wall,this paper focuses on the solution at the outset;it presents a method to find vulnerabilities by analyzing the source codes.The concept of validated tree is developed to track variables referenced by database operations in scripts.By checking whether these variables are influenced by outside inputs,the database operations are proved to be secure or not.This method has advantages of high accuracy and efficiency as well as low costs,and it is universal to any type of web application platforms.It is implemented by the software code vulnerabilities of SQL injection detector(CVSID).The validity and efficiency are demonstrated with an example.展开更多
Bottlenecks, the key ingredients for improving the performances of the production networks, have been profoundly studied during the last decade. Yet, because of the complexity of the research results, there is still a...Bottlenecks, the key ingredients for improving the performances of the production networks, have been profoundly studied during the last decade. Yet, because of the complexity of the research results, there is still a significant gap between theory and practice. In this paper, we review various bottleneck definitions, detection methods and the asymptotic results and provide a practical guidance for recognizing and utilizing the bottlenecks in production networks. Queueing theory works as the mathematical foundation in our study. Various definitions of the bottlenecks are classified as either Performance in Processing (PIP) based or sensitivity based definitions, which reflect the preferences of the managers. Detection methods are surveyed closely based on the definitions. These methods are used to recognize the bottlenecks and to provide diagnosis results to managers. Comparisons show that different detection methods may lead to vastly different conclusions. The recognition of the bottlenecks has another advantage: the ultimate phenomena of the bottlenecks can greatly reduce the computation complexity in calculating the system performances. Bottlenecks based approximation and asymptotic results are studied to exhibit the contribution of bottlenecks in performance estimation and theoretical analysis.展开更多
Resource planning for a remanufacturing system is in general extremely difficult in terms of problem size,uncertainties,complicated constraints,etc.In this paper,we present a new method based on constrained ordinal op...Resource planning for a remanufacturing system is in general extremely difficult in terms of problem size,uncertainties,complicated constraints,etc.In this paper,we present a new method based on constrained ordinal optimization(COO)for remanufacturing planning.The key idea of our method is to estimate the feasibility of plans by machine learning and to select a subset with the estimated feasibility based on the procedure of horse racing with feasibility model(HRFM).Numerical testing shows that our method is efficient and effective for selecting good plans with high probability.It is thus a scalable optimization method for large scale remanufacturing planning problems with complicated stochastic constraints.展开更多
基金supported by a contract between General Motors Company and Tsinghua University,National Natural Science Foundation of China(61425027,60736027,61021063,61074034,61174105)
文摘In this paper, we study a class of manufacturing systems which consist of multiple plants and each of the plants has capability of producing multiple distinct products. The production lines of a certain plant may switch between producing different kinds of products in a time-sharing mode. We optimize the capacity configuration of such a system s production lines with the objective to maximize the overall profit in the capacity planning horizon. Uncertain demand is incorporated in the model to achieve a robust configuration solution. The optimization problem is formulated as a nonlinear polynomial stochastic programming problem, which is difficult to be efficiently solved due to demand uncertainties and large search space. We show the NP-hardness of the problem first, and then apply ordinal optimization(OO) method to search for good enough designs with high probability. At lower level, an mixed integer programming(MIP) solving tool is employed to evaluate the performance of a design under given demand profile.
基金Project supported by the National Natural Science Foundation of0 China (Nos. 60274011 and 60574067), and the Program for NewCentury Excellent Talents in University (No. NCET-04-0094), China
文摘The Fork-Join program consisting of K parallel tasks is a useful model for a large number of computing applications. When the parallel processor has multi-channels, later tasks may finish execution earlier than their earlier tasks and may join with tasks from other programs. This phenomenon is called exchangeable join (EJ), which introduces correlation to the task’s service time. In this work, we investigate the response time of multiprocessor systems with EJ with a new approach. We analyze two aspects of this kind of systems: exchangeable join (EJ) and the capacity constraint (CC). We prove that the system response time can be effectively reduced by EJ, while the reduced amount is constrained by the capacity of the multiprocessor. An upper bound model is constructed based on this analysis and a quick estimation algorithm is proposed. The approximation formula is verified by extensive simulation results, which show that the relative error of approximation is less than 5%.
文摘The evaluation system is significant for assessment of technologies, experiments, energy cost and effectiveness, especially for the complicated engineering systems, such as energy systems, weapon systems and spacecraft systems. However, as engineering systems become more and more distributed and heterogeneous, evaluation frameworks need to be more universal,distributed and interactive. In this paper, we compare several typical evaluation frameworks and propose a novel evaluation framework based on multi-agent technology. We provide two case studies, indoor comfort system and technology assessment of spacecraft systems, respectively. The results show that the proposed framework can work efficiently.
基金Supported in part by the National Natural Science Foundation of China(Grant Nos.60736027,60704033)the National High Technology Research and Development Program of China(863 Program)(Grant No.2007AA04Z154)111 International Collaboration Program of China and Program for New Century Talents of Education Ministry of China(Grant No.NCET-08-0432)
文摘Operation scheduling for a class of production systems with"instantly consumed"products is very important.It is challenging to satisfy the real time system demand and to consider the realizability of the production schedules.This paper formulates a new model for optimization based production scheduling problems with integral constraints.Based on the detailed analysis of the production rate constraints,it is proved that this type of optimization problems is equivalent to a smooth nonlinear programming problem.The reachable upper and lower bounds of the production amount in every period can be expressed as functions of two variables,i.e.,the production rate at the start and end of that period.It is also proved that the gradients of these functions are monotonic,and their convexity or concavity is guaranteed.When the production cost function is convex,this type of optimization problems is equivalent to a convex programming problem.With the above analysis,a two-stage solution method is developed to solve the production scheduling problems with integral constraints,and in many applications the global optimal solution can be obtained efficiently.With the new model and solution method,the difficulties caused by the constraints on production rate can be overcome and the optimal schedule can be obtained with the real time system demand satisfied.Numerical testing for scheduling of electric power production systems is performed and the testing results are discussed.It is demonstrated that the new model and solution method are effective.
基金The research is supported in part by National Natural Science Foundation (No. 60574087, 60574064) and the "111 International Collaboration Project" of China.
文摘Buildings worldwide account for nearly 40%of global energy consumption.The biggest energy consumer in buildings is the heating,ventilation and air conditioning(HVAC)systems.In HVAC systems,chillers account for a major portion of the energy consumption.Maintaining chillers in good conditions through early fault detection and diagnosis is thus a critical issue.In this paper,the fault detection and diagnosis for an air-cooled chiller with air coming from outside in variable flow rates is studied.The problem is difficult since the air-cooled chiller is operating under major uncertainties including the cooling load,and the air temperature and flow rate.A potential method to overcome the difficulty caused by the uncertainties is to perform fault detection and diagnosis based on a gray-box model with parameters regarded as constants.The method is developed and verified by us in another paper for a water-cooled chiller with the uncertainty of cooling load.The verification used a Kalman filter to predict parameters of a gray-box model and statistical process control(SPC)for measuring and analyzing their variations for fault detection and diagnosis.The gray-box model in the method,however,requires that the air temperature and flow rate be nearly constant.By introducing two new parameters and deleting data points with low air flow rate,the requirement can be satisfied and the method can then be applicable for an air-cooled chiller.The simulation results show that the method with the revised model and some data points dropped improved the fault detection and diagnosis(FDD)performance greatly.It can detect both sudden and gradual air-cooled chiller capacity degradation and sensor faults as well as their recoveries.
基金Supported by Foundations of SiChuan Educational Committee under Grant No 13ZB0198the National Natural Science Foundation of China under Grant Nos 61104224,81373531,61104143 and 61573107The Science and Technology Fund Project of SWPU(2013XJR011)
文摘The influence of a node in a network can be characterized by its macroscopic properties such as eigenvector centrality. An issue of significant theoretical and practical interest is to modify the influence or roles of the nodes in a network, and recent advances indicate that this can be achieved by just controlling a subset of nodes: the socalled controllers. However, the relationship between the structural properties of a network and its controllability, e.g., the control of node importance, is still not well understood. Here we systematically" explore this relationship by constructing scale-free networks with a fixed degree sequence and tunable network characteristics. We calculate the relative size (nc*) of the minimai controlling set required to controi the importance of each individual node in a network. It is found that while clustering has no significant impact on nc*, changes in degree-degree correlations, heterogeneity and the average degree of networks demonstrate a discernible impact on its controllability.
基金This work was supported in part by the National Key Research and Development Program of China(No.2016YFB0901900)the National Natural Science Foundation of China under grants(No.61673229)the 111 International Collaboration Project of China(No.BP2018006).
文摘The adoption and usage of electric vehicles(EVs)have emerged recently due to the increasing concerns on the greenhouse gas issues and energy revolution.As a part of the smart grid,EVs can provide valuable ancillary services beyond consumers of electricity.However,EVs are gradually considered as nonnegligible loads due to their increasing penetration,which may result in negative effects such as voltage deviations,lines saturation,and power losses.Relationship and interaction among EVs,charging stations,and micro grid have to be considered in the next generation of smart grid.Therefore,the topic of smart charging has been the focus of many works where a wide range of control methods have been developed.As one of the bases of simulation,the EV charging behavior and characteristics have also become the focus of many studies.In this work,we review the charging behavior of EVs from the aspects of data,model,and control.We provide the links for most of the data sets reviewed in this work,based on which interested researchers can easily access these data for further investigation.
基金This work is supported by Key R&D Project of China under Grant No.2017YFC0704100,2016YFB0901900National Natural Science Foun-dation of China under Grant No.61425024,the 111 International Col-laboration Program of China under Grant No.BP2018006+2 种基金2019 Major Science and Technology Program for the Strategic Emerging Industries of Fuzhou under Grant No.2019-Z-1in part by the BNRist Pro-gram under Grant No.BNR2019TD01009the National Innovation Cen-ter of High Speed Train R&D project(CX/KJ-2020-0006).
文摘Fire detection in buildings is crucial for people’s lives and property.Conventional temperature and smoke sen-sors have many disadvantages:the limited cover range;detection delays;the difficulty in distinguishing smoke and fire.Recently,research on convolutional neural networks(CNN)for fire image detection has become a hot topic.However,existing fire classification and object detection methods are often interfered with by flash-lights,red objects and the high-brightness background,resulting in a high false alarm rate.Besides,light and lamps often exist in buildings.To address this issue,this paper focuses on introducing scene prior knowledge and causal inference mechanisms to suppress the lamp disturbance.Firstly,we train the YoloV3 network to detect and recognize lamps.Secondly,to reduce the dataset bias,we mask the lamp regions with the pro-posed Local Grabcut segmentation method.Last,compared with direct fire classification methods,our proposed methods reduce about 34.6%false alarm rate based on InceptionV4 networks.The experimental results verify the effectiveness among different CNN architectures(Resnet101,Firenet,Densenet121).The code is online at https://github.com/kailaisun/fire-detection-without-lamp.
基金Supported by the National Natural Science Foundation of China (Grant Nos. 60274011, 60574067, 60704008, 60736027, 60721003, 90924001)the New Century Excellent Talents in University (Grant No. NCET-04-0094)+1 种基金the Specialized Research Fund for the Doctoral Program of Higher Education (Grant No. 20070003110)the Programme of Introducing Talents of Discipline to Universities (the National 111 International Collaboration Projects) (Grant No. B06002)
基金supported in part by the National Key Research and Development Program of China(No.2016YFB0901900)the National Natural Science Foundation of China(Nos.62073182 and 61673229)the 111 International Collaboration Project of China(No.BP2018006).
文摘The matching between dynamic supply of renewable power generation and flexible charging demand ofthe Electric Vehicles (EVs) can not only increase the penetration of renewables but also reduce the load to the stateelectric power grid. The challenges herein are the curse of dimensionality, the multiple decision making stagesinvolved, and the uncertainty of both the supply and demand sides. Event-Based Optimization (EBO) provides a newway to solve large-scale Markov decision process. Considering different spatial scales, we develop a bi-level EBOmodel in this paper which can both catch the changes on the macro and micro levels. By proper definition, the sizeof event space stays fixed with the scale of the problem, which shows good scalability in online optimization. Then abi-level Q-learning method is developed to solve the problem iteratively. We demonstrate the performance of themethod by numerical examples. Our method outperforms other methods both in performance and scalability.
基金supported by the National Natural Science Foundation of China (Grant Nos.60574064,60736027).
文摘The optimal control of a Markov jump linear quadratic model with controlled jump probabilities of modes is investigated.Two kinds of mode control policies,i.e.,open-loop control policy and closed-loop control policy,are considered.Using the concepts of policy iteration and performance potential,the sufficient condition needed for the optimal closed-loop control policy to perform better than the optimal open-loop control policy is proposed.The condition is helpful for the design of an optimal controller.Furthermore,an efficient algorithm to construct a closed-loop control policy,which is better than the optimal open-loop control policy,is given with policy iteration.
文摘If the decade of 1990s were the period of Globalization,the first ten years of this new century can certainly be characterized as the age of Connectedness.Through“connectedness”the world becomes Friedmanianly flat,people are enabled,informed,and equipped to deal with a complex,hot,and crowded world.Not only there is the ubiquitous Internet from which all of us are increasingly dependent,but there are many other kinds of networks,social,commercial,economic,and military that drive our civilization.
基金supported by the National Natural Science Foundation of China (Grant No.60574087)the Hi-Tech Research and Development Program of China (Nos.2007AA01Z475,2007AA01Z480,2007AA01Z464)the 111 International Collaboration Program of China.
文摘SQL injection poses a major threat to the application level security of the database and there is no systematic solution to these attacks.Different from traditional run time security strategies such as IDS and fire-wall,this paper focuses on the solution at the outset;it presents a method to find vulnerabilities by analyzing the source codes.The concept of validated tree is developed to track variables referenced by database operations in scripts.By checking whether these variables are influenced by outside inputs,the database operations are proved to be secure or not.This method has advantages of high accuracy and efficiency as well as low costs,and it is universal to any type of web application platforms.It is implemented by the software code vulnerabilities of SQL injection detector(CVSID).The validity and efficiency are demonstrated with an example.
基金This work was supported by NSFC Grant. No. (60074012,60274011) and NCET-04-0094 program.
文摘Bottlenecks, the key ingredients for improving the performances of the production networks, have been profoundly studied during the last decade. Yet, because of the complexity of the research results, there is still a significant gap between theory and practice. In this paper, we review various bottleneck definitions, detection methods and the asymptotic results and provide a practical guidance for recognizing and utilizing the bottlenecks in production networks. Queueing theory works as the mathematical foundation in our study. Various definitions of the bottlenecks are classified as either Performance in Processing (PIP) based or sensitivity based definitions, which reflect the preferences of the managers. Detection methods are surveyed closely based on the definitions. These methods are used to recognize the bottlenecks and to provide diagnosis results to managers. Comparisons show that different detection methods may lead to vastly different conclusions. The recognition of the bottlenecks has another advantage: the ultimate phenomena of the bottlenecks can greatly reduce the computation complexity in calculating the system performances. Bottlenecks based approximation and asymptotic results are studied to exhibit the contribution of bottlenecks in performance estimation and theoretical analysis.
基金The research presented in this paper was supported in part by the National Natural Science Foundation of China(Grant Nos.60274011,60574087,60704008,and 90924001)the National High Technology Research and Development Program of China(Grant No.2007AA04Z154)+2 种基金the Program for New Century Excellent Talents in University(NCET-04-0094)the Specialized Research Fund for the Doctoral Program of Higher Education(20070003110)the 111 International Collaboration Project(B06002).
文摘Resource planning for a remanufacturing system is in general extremely difficult in terms of problem size,uncertainties,complicated constraints,etc.In this paper,we present a new method based on constrained ordinal optimization(COO)for remanufacturing planning.The key idea of our method is to estimate the feasibility of plans by machine learning and to select a subset with the estimated feasibility based on the procedure of horse racing with feasibility model(HRFM).Numerical testing shows that our method is efficient and effective for selecting good plans with high probability.It is thus a scalable optimization method for large scale remanufacturing planning problems with complicated stochastic constraints.