Satellite Component Layout Optimization(SCLO) is crucial in satellite system design.This paper proposes a novel Satellite Three-Dimensional Component Assignment and Layout Optimization(3D-SCALO) problem tailored to en...Satellite Component Layout Optimization(SCLO) is crucial in satellite system design.This paper proposes a novel Satellite Three-Dimensional Component Assignment and Layout Optimization(3D-SCALO) problem tailored to engineering requirements, aiming to optimize satellite heat dissipation while considering constraints on static stability, 3D geometric relationships between components, and special component positions. The 3D-SCALO problem is a challenging bilevel combinatorial optimization task, involving the optimization of discrete component assignment variables in the outer layer and continuous component position variables in the inner layer,with both influencing each other. To address this issue, first, a Mixed Integer Programming(MIP) model is proposed, which reformulates the original bilevel problem into a single-level optimization problem, enabling the exploration of a more comprehensive optimization space while avoiding iterative nested optimization. Then, to model the 3D geometric relationships between components within the MIP framework, a linearized 3D Phi-function method is proposed, which handles non-overlapping and safety distance constraints between cuboid components in an explicit and effective way. Subsequently, the Finite-Rectangle Method(FRM) is proposed to manage 3D geometric constraints for complex-shaped components by approximating them with a finite set of cuboids, extending the applicability of the geometric modeling approach. Finally, the feasibility and effectiveness of the proposed MIP model are demonstrated through two numerical examples"and a real-world engineering case, which confirms its suitability for complex-shaped components and real engineering applications.展开更多
In the traditional environment, the factors for considering the location of the waste transfer station and the landfill are relatively fixed, and the scale of the problem is small. But in Internet of Things(IoT) envir...In the traditional environment, the factors for considering the location of the waste transfer station and the landfill are relatively fixed, and the scale of the problem is small. But in Internet of Things(IoT) environment, the waste storage in the household waste can be monitored in real time, the environmental data can be collected by means of emerging information technology, and the residents are more sensitive to the environmental pollution of the waste. Under such conditions, the method for location of traditional waste disposal facilities needs to be redeveloped to obtain a waste transfer station and landfill site that are suitable for the IoT environment. For this reason, a two-objective integer programming model is designed. The two objectives are lowest cost and minimum impact of waste on residents. The expectations of city managers and residents are considered into the modeling. Through the simulation experiments on different scale problems, the integration method for integer programming model and simulation system is verified to solve the location of waste transfer stations in IoT environment.展开更多
In this paper, we not only construct the confidence region for parameters in a mixed integer-valued autoregressive process using the empirical likelihood method, but also establish the empirical log-likelihood ratio s...In this paper, we not only construct the confidence region for parameters in a mixed integer-valued autoregressive process using the empirical likelihood method, but also establish the empirical log-likelihood ratio statistic and obtain its limiting distribution. And then, via simulation studies we give coverage probabilities for the parameters of interest. The results show that the empirical likelihood method performs very well.展开更多
Queen problems are unstructured problems, whose solution scheme can be applied in the actual job scheduling. As for the n-queen problem, backtracking algorithm is considered as an effective approach when the value of ...Queen problems are unstructured problems, whose solution scheme can be applied in the actual job scheduling. As for the n-queen problem, backtracking algorithm is considered as an effective approach when the value of n is small. However, in case the value of n is large, the phenomenon of combination explosion is expected to occur. In order to solve the aforementioned problem, queen problems are firstly converted into the problem of function optimization with constraints, and then the corresponding mathematical model is established. Afterwards, the n-queen problem is solved by constructing the genetic operators and adaption functions using the integer coding based on the population search technology of the evolutionary computation. The experimental results demonstrate that the proposed algorithm is endowed with rapid calculation speed and high efficiency, and the model presents simple structure and is readily implemented.展开更多
In this document, we present new techniques for near-lossless and lossy compression of SAR imagery saved in PNG and binary formats of magnitude and phase data based on the application of transforms, dimensionality red...In this document, we present new techniques for near-lossless and lossy compression of SAR imagery saved in PNG and binary formats of magnitude and phase data based on the application of transforms, dimensionality reduction methods, and lossless compression. In particular, we discuss the use of blockwise integer to integer transforms, subsequent application of a dimensionality reduction method, and Burrows-Wheeler based lossless compression for the PNG data and the use of high correlation based modeling of sorted transform coefficients for the raw floating point magnitude and phase data. The gains exhibited are substantial over the application of different lossless methods directly on the data and competitive with existing lossy approaches. The methods presented are effective for large scale processing of similar data formats as they are heavily based on techniques which scale well on parallel architectures.展开更多
Production scheduling has a major impact on the productivity of the manufacturing process. Recently, scheduling problems with deteriorating jobs have attracted increasing attentions from researchers. In many practical...Production scheduling has a major impact on the productivity of the manufacturing process. Recently, scheduling problems with deteriorating jobs have attracted increasing attentions from researchers. In many practical situations,it is found that some jobs fail to be processed prior to the pre-specified thresholds,and they often consume extra deteriorating time for successful accomplishment. Their processing times can be characterized by a step-wise function. Such kinds of jobs are called step-deteriorating jobs. In this paper,parallel machine scheduling problem with stepdeteriorating jobs( PMSD) is considered. Due to its intractability,four different mixed integer programming( MIP) models are formulated for solving the problem under consideration. The study aims to investigate the performance of these models and find promising optimization formulation to solve the largest possible problem instances. The proposed four models are solved by commercial software CPLEX. Moreover,the near-optimal solutions can be obtained by black-box local-search solver LocalS olver with the fourth one. The computational results show that the efficiencies of different MIP models depend on the distribution intervals of deteriorating thresholds, and the performance of LocalS olver is clearly better than that of CPLEX in terms of the quality of the solutions and the computational time.展开更多
Approaches based on integer linear programming have been recently proposed for topology optimization in wireless sensor networks. They are, however, based on over-theoretical, unrealistic models. Our aim is to show th...Approaches based on integer linear programming have been recently proposed for topology optimization in wireless sensor networks. They are, however, based on over-theoretical, unrealistic models. Our aim is to show that it is possible to accommodate realistic models for energy consumption and communication protocols into integer linear programming. We analyze the maximum lifetime broadcasting topology problem and we present realistic models that are also shown to provide efficient and practical solving tools. We present a strategy to substantially speed up the convergence of the solving process of our algorithm. This strategy introduces a practical drawback, however, in the characteristics of the optimal solutions retrieved. A method to overcome this drawback is discussed. Computational experiments are reported.展开更多
This paper gives integer linear programming (ILP) models for scheduling the League Phase of one of the most popular professional club competitions in the world, UEFA Champion’s League. There are 36 teams in the compe...This paper gives integer linear programming (ILP) models for scheduling the League Phase of one of the most popular professional club competitions in the world, UEFA Champion’s League. There are 36 teams in the competition, but each team plays only 8 other teams in the League Phase. Thus, the difficulty or ease of a team’s opponents, known as strength of schedule (SOS), compared to other teams will be different. Our main ILP model aims to minimize the maximum difference between SOS of any two teams, thus making the schedule as fair as possible. We also give a model for creating a timetable of all the matchups obtained by the first model. The models were implemented and tested using optimization software AMPL. Our main model obtained a schedule with a difference 0.4 between the highest and the lowest SOS, while that difference is 19 for the actual 2024-2025 competition. Thus, our model returns a schedule that is significantly fairer compared to the actual competition.展开更多
Ensuring the safe evacuation of miners during fire emergencies in the shortest possible time is one of the most critical aspects of underground mining operations.Despite advances in mining evacuation methods,little re...Ensuring the safe evacuation of miners during fire emergencies in the shortest possible time is one of the most critical aspects of underground mining operations.Despite advances in mining evacuation methods,little research has been conducted on mine vehicles in this context.This study proposed a vehicle-augmented evacuation integer programming(VEIP)model to minimize the total evacuation cost as a function of the required evacuation time during fire emergencies.This approach aims to minimize the risk of miners being exposed to dangerous fire conditions by strategically integrating mine vehicles into the evacuation procedure.The approach determines the optimal evacuation path for each miner,considering factors such as available mine vehicles,miners’locations,refuge chambers,and fresh-air bases.To validate the effectiveness of the developed VEIP model,a case study was conducted using the mine layout of the Turquoise Ridge Underground Mine in the United States.Furthermore,a statistical comparison was conducted between the VEIP model and the evacuation integer programming(EIP)model,tailored to evacuation on foot,to emphasize vehicles’influence on the evacuation process.The results showed that integrating mine vehicles into evacuation procedures significantly reduces the total evacuation time.A cost savings analysis in the VEIP model revealed that the evacuation time savings increase exponentially as the number of miners present during evacuation increases.The potential benefits of using mine vehicles to improve the efficiency of evacuation from underground mine fires were highlighted in this study.展开更多
Enhancing traffic efficiency and alleviating(even circumventing)traffic congestion with advanced traffic signal control(TSC)strategies are always the main issues to be addressed in urban transportation systems.Since m...Enhancing traffic efficiency and alleviating(even circumventing)traffic congestion with advanced traffic signal control(TSC)strategies are always the main issues to be addressed in urban transportation systems.Since model predictive control(MPC)has a lot of advantages in modeling complex dynamic systems,it has been widely studied in traffic signal control over the past 20 years.There is a need for an in-depth understanding of MPC-based TSC methods for traffic networks.Therefore,this paper presents the motivation of using MPC for TSC and how MPC-based TSC approaches are implemented to manage and control the dynamics of traffic flows both in urban road networks and freeway networks.Meanwhile,typical performance evaluation metrics,solution methods,examples of simulations,and applications related to MPC-based TSC approaches are reported.More importantly,this paper summarizes the recent developments and the research trends in coordination and control of traffic networks with MPC-based TSC approaches.Remaining challenges and open issues are discussed towards the end of this paper to discover potential future research directions.展开更多
The output-signal models and impulse response shaping(IRS)functions of semiconductor detectors are important for establishing high-precision measurement systems.In this paper,an output-signal model for semiconductor d...The output-signal models and impulse response shaping(IRS)functions of semiconductor detectors are important for establishing high-precision measurement systems.In this paper,an output-signal model for semiconductor detector systems is proposed.According to the proposed model,a multistage cascade deconvolution IRS algorithm was developed using the C-R inverse system,R-C inverse system,and differentiator system.The silicon drift detector signals acquired from the analog-to-digital converter were tested.The experimental results indicated that the shaped pulses obtained using the proposed model had no undershoot,and the average peak base width of the output shaped pulses was reduced by 36%compared with that for a simple model proposed in a previous work[1].Offline processing results indicated that compared with the traditional IRS algorithm,the average peak base width of the output shaped pulses obtained using the proposed algorithm was reduced by 11%,and the total elapsed time required for pulse shaping was reduced by 26%.The proposed algorithm avoids recursive calculation.If the sampling frequency of the digital system reaches 100 MHz,the proposed algorithm can be simplified to integer arithmetic.The proposed IRS algorithm can be applied to high-resolution energy spectrum analysis,highcounting rate energy spectrum correction,and coincidence and anti-coincidence measurements.展开更多
With the rapid development of highway construction and formation of the highway network in China,the man- agement of pavement maintenance and rehabilitation （MR） activities has become important.In this paper,four di...With the rapid development of highway construction and formation of the highway network in China,the man- agement of pavement maintenance and rehabilitation （MR） activities has become important.In this paper,four discrete optimization models are proposed for different parties involved in the management system： government,highway agent,con- tractor and the common users.These four optimal decision models are formulated as linear integer programming problems with binary decision variables.The objective function and constraints are based on the pavement performance and prediction model using the pavement condition index （PCI）.Numerical experiments are carried out with the data from a highway system in Sichuan Province which show the feasibility and effectiveness of the proposed models.展开更多
基金supported by the National Natural Science Foundation of China(No.92371206)the Postgraduate Scientific Research Innovation Project of Hunan Province,China(No.CX2023063).
文摘Satellite Component Layout Optimization(SCLO) is crucial in satellite system design.This paper proposes a novel Satellite Three-Dimensional Component Assignment and Layout Optimization(3D-SCALO) problem tailored to engineering requirements, aiming to optimize satellite heat dissipation while considering constraints on static stability, 3D geometric relationships between components, and special component positions. The 3D-SCALO problem is a challenging bilevel combinatorial optimization task, involving the optimization of discrete component assignment variables in the outer layer and continuous component position variables in the inner layer,with both influencing each other. To address this issue, first, a Mixed Integer Programming(MIP) model is proposed, which reformulates the original bilevel problem into a single-level optimization problem, enabling the exploration of a more comprehensive optimization space while avoiding iterative nested optimization. Then, to model the 3D geometric relationships between components within the MIP framework, a linearized 3D Phi-function method is proposed, which handles non-overlapping and safety distance constraints between cuboid components in an explicit and effective way. Subsequently, the Finite-Rectangle Method(FRM) is proposed to manage 3D geometric constraints for complex-shaped components by approximating them with a finite set of cuboids, extending the applicability of the geometric modeling approach. Finally, the feasibility and effectiveness of the proposed MIP model are demonstrated through two numerical examples"and a real-world engineering case, which confirms its suitability for complex-shaped components and real engineering applications.
基金Supported by the National Natural Science Foundation of China(71531009).
文摘In the traditional environment, the factors for considering the location of the waste transfer station and the landfill are relatively fixed, and the scale of the problem is small. But in Internet of Things(IoT) environment, the waste storage in the household waste can be monitored in real time, the environmental data can be collected by means of emerging information technology, and the residents are more sensitive to the environmental pollution of the waste. Under such conditions, the method for location of traditional waste disposal facilities needs to be redeveloped to obtain a waste transfer station and landfill site that are suitable for the IoT environment. For this reason, a two-objective integer programming model is designed. The two objectives are lowest cost and minimum impact of waste on residents. The expectations of city managers and residents are considered into the modeling. Through the simulation experiments on different scale problems, the integration method for integer programming model and simulation system is verified to solve the location of waste transfer stations in IoT environment.
基金Supported by National Natural Science Foundation of China(11731015,11571051,J1310022,11501241)Natural Science Foundation of Jilin Province(20150520053JH,20170101057JC,20180101216JC)+2 种基金Program for Changbaishan Scholars of Jilin Province(2015010)Science and Technology Program of Jilin Educational Department during the "13th Five-Year" Plan Period(2016-399)Science and Technology Research Program of Education Department in Jilin Province for the 13th Five-Year Plan(2016213)
文摘In this paper, we not only construct the confidence region for parameters in a mixed integer-valued autoregressive process using the empirical likelihood method, but also establish the empirical log-likelihood ratio statistic and obtain its limiting distribution. And then, via simulation studies we give coverage probabilities for the parameters of interest. The results show that the empirical likelihood method performs very well.
文摘Queen problems are unstructured problems, whose solution scheme can be applied in the actual job scheduling. As for the n-queen problem, backtracking algorithm is considered as an effective approach when the value of n is small. However, in case the value of n is large, the phenomenon of combination explosion is expected to occur. In order to solve the aforementioned problem, queen problems are firstly converted into the problem of function optimization with constraints, and then the corresponding mathematical model is established. Afterwards, the n-queen problem is solved by constructing the genetic operators and adaption functions using the integer coding based on the population search technology of the evolutionary computation. The experimental results demonstrate that the proposed algorithm is endowed with rapid calculation speed and high efficiency, and the model presents simple structure and is readily implemented.
文摘In this document, we present new techniques for near-lossless and lossy compression of SAR imagery saved in PNG and binary formats of magnitude and phase data based on the application of transforms, dimensionality reduction methods, and lossless compression. In particular, we discuss the use of blockwise integer to integer transforms, subsequent application of a dimensionality reduction method, and Burrows-Wheeler based lossless compression for the PNG data and the use of high correlation based modeling of sorted transform coefficients for the raw floating point magnitude and phase data. The gains exhibited are substantial over the application of different lossless methods directly on the data and competitive with existing lossy approaches. The methods presented are effective for large scale processing of similar data formats as they are heavily based on techniques which scale well on parallel architectures.
基金National Natural Science Foundation of China(No.51405403)the Fundamental Research Funds for the Central Universities,China(No.2682014BR019)the Scientific Research Program of Education Bureau of Sichuan Province,China(No.12ZB322)
文摘Production scheduling has a major impact on the productivity of the manufacturing process. Recently, scheduling problems with deteriorating jobs have attracted increasing attentions from researchers. In many practical situations,it is found that some jobs fail to be processed prior to the pre-specified thresholds,and they often consume extra deteriorating time for successful accomplishment. Their processing times can be characterized by a step-wise function. Such kinds of jobs are called step-deteriorating jobs. In this paper,parallel machine scheduling problem with stepdeteriorating jobs( PMSD) is considered. Due to its intractability,four different mixed integer programming( MIP) models are formulated for solving the problem under consideration. The study aims to investigate the performance of these models and find promising optimization formulation to solve the largest possible problem instances. The proposed four models are solved by commercial software CPLEX. Moreover,the near-optimal solutions can be obtained by black-box local-search solver LocalS olver with the fourth one. The computational results show that the efficiencies of different MIP models depend on the distribution intervals of deteriorating thresholds, and the performance of LocalS olver is clearly better than that of CPLEX in terms of the quality of the solutions and the computational time.
文摘Approaches based on integer linear programming have been recently proposed for topology optimization in wireless sensor networks. They are, however, based on over-theoretical, unrealistic models. Our aim is to show that it is possible to accommodate realistic models for energy consumption and communication protocols into integer linear programming. We analyze the maximum lifetime broadcasting topology problem and we present realistic models that are also shown to provide efficient and practical solving tools. We present a strategy to substantially speed up the convergence of the solving process of our algorithm. This strategy introduces a practical drawback, however, in the characteristics of the optimal solutions retrieved. A method to overcome this drawback is discussed. Computational experiments are reported.
文摘This paper gives integer linear programming (ILP) models for scheduling the League Phase of one of the most popular professional club competitions in the world, UEFA Champion’s League. There are 36 teams in the competition, but each team plays only 8 other teams in the League Phase. Thus, the difficulty or ease of a team’s opponents, known as strength of schedule (SOS), compared to other teams will be different. Our main ILP model aims to minimize the maximum difference between SOS of any two teams, thus making the schedule as fair as possible. We also give a model for creating a timetable of all the matchups obtained by the first model. The models were implemented and tested using optimization software AMPL. Our main model obtained a schedule with a difference 0.4 between the highest and the lowest SOS, while that difference is 19 for the actual 2024-2025 competition. Thus, our model returns a schedule that is significantly fairer compared to the actual competition.
基金funded by the National Institute for Occupational Health and Safety under grant U60OH012351an Artificially Intelligent Mining Systems(AIMS)Capacity Building Project under contract number 75D30119C06044 for safer and healthier automated operations.
文摘Ensuring the safe evacuation of miners during fire emergencies in the shortest possible time is one of the most critical aspects of underground mining operations.Despite advances in mining evacuation methods,little research has been conducted on mine vehicles in this context.This study proposed a vehicle-augmented evacuation integer programming(VEIP)model to minimize the total evacuation cost as a function of the required evacuation time during fire emergencies.This approach aims to minimize the risk of miners being exposed to dangerous fire conditions by strategically integrating mine vehicles into the evacuation procedure.The approach determines the optimal evacuation path for each miner,considering factors such as available mine vehicles,miners’locations,refuge chambers,and fresh-air bases.To validate the effectiveness of the developed VEIP model,a case study was conducted using the mine layout of the Turquoise Ridge Underground Mine in the United States.Furthermore,a statistical comparison was conducted between the VEIP model and the evacuation integer programming(EIP)model,tailored to evacuation on foot,to emphasize vehicles’influence on the evacuation process.The results showed that integrating mine vehicles into evacuation procedures significantly reduces the total evacuation time.A cost savings analysis in the VEIP model revealed that the evacuation time savings increase exponentially as the number of miners present during evacuation increases.The potential benefits of using mine vehicles to improve the efficiency of evacuation from underground mine fires were highlighted in this study.
基金supported in part by the National Natural Science Foundation of China(61603154,61773343,61621002,61703217)the Natural Science Foundation of Zhejiang Province(LY15F030021,LY19F030014)Open Research Project of the State Key Laboratory of Industrial Control Technology,Zhejiang University,China(ICT1800407)
文摘Enhancing traffic efficiency and alleviating(even circumventing)traffic congestion with advanced traffic signal control(TSC)strategies are always the main issues to be addressed in urban transportation systems.Since model predictive control(MPC)has a lot of advantages in modeling complex dynamic systems,it has been widely studied in traffic signal control over the past 20 years.There is a need for an in-depth understanding of MPC-based TSC methods for traffic networks.Therefore,this paper presents the motivation of using MPC for TSC and how MPC-based TSC approaches are implemented to manage and control the dynamics of traffic flows both in urban road networks and freeway networks.Meanwhile,typical performance evaluation metrics,solution methods,examples of simulations,and applications related to MPC-based TSC approaches are reported.More importantly,this paper summarizes the recent developments and the research trends in coordination and control of traffic networks with MPC-based TSC approaches.Remaining challenges and open issues are discussed towards the end of this paper to discover potential future research directions.
基金supported by the National Natural Science Foundation of China(Nos.11975060,12005026,and 12075038)the Major Science and Technology Project in Sichuan Province(No.19ZDZD0137)the Sichuan Science and Technology Program(No.2020YFG0019).
文摘The output-signal models and impulse response shaping(IRS)functions of semiconductor detectors are important for establishing high-precision measurement systems.In this paper,an output-signal model for semiconductor detector systems is proposed.According to the proposed model,a multistage cascade deconvolution IRS algorithm was developed using the C-R inverse system,R-C inverse system,and differentiator system.The silicon drift detector signals acquired from the analog-to-digital converter were tested.The experimental results indicated that the shaped pulses obtained using the proposed model had no undershoot,and the average peak base width of the output shaped pulses was reduced by 36%compared with that for a simple model proposed in a previous work[1].Offline processing results indicated that compared with the traditional IRS algorithm,the average peak base width of the output shaped pulses obtained using the proposed algorithm was reduced by 11%,and the total elapsed time required for pulse shaping was reduced by 26%.The proposed algorithm avoids recursive calculation.If the sampling frequency of the digital system reaches 100 MHz,the proposed algorithm can be simplified to integer arithmetic.The proposed IRS algorithm can be applied to high-resolution energy spectrum analysis,highcounting rate energy spectrum correction,and coincidence and anti-coincidence measurements.
基金Project supported by the National Natural Science Foundation of China (Grant No.70671064)
文摘With the rapid development of highway construction and formation of the highway network in China,the man- agement of pavement maintenance and rehabilitation （MR） activities has become important.In this paper,four discrete optimization models are proposed for different parties involved in the management system： government,highway agent,con- tractor and the common users.These four optimal decision models are formulated as linear integer programming problems with binary decision variables.The objective function and constraints are based on the pavement performance and prediction model using the pavement condition index （PCI）.Numerical experiments are carried out with the data from a highway system in Sichuan Province which show the feasibility and effectiveness of the proposed models.
