Prestressed concrete structures are main conformati on for the construction of high way bridges. The quality of prestressed concrete s tructures is mainly affected by the tensile strength of prestressing strand. In or...Prestressed concrete structures are main conformati on for the construction of high way bridges. The quality of prestressed concrete s tructures is mainly affected by the tensile strength of prestressing strand. In order to attain the purpose of economic design and long life span of prestressin g strand, the less relaxation property of strand type is suitable for constructi on and usage. Thus, the research and development of prestressing strand is requi red to reach the goals of high tensile strength and low relaxation. To ensure th e required quality of prestressing strand, the strand pull test and long period relaxation test are two important items for the quality assurance. There are thr ee specific items of the tensile strength test are belong to larger-the-better quality type. The quality type of smaller-the-better is for the long period r elaxation test. However, many existing methods are able to measure process capab ility for product with single quality characteristic and cannot be applied to mo st products with multiple properties. Thus, the indices of C pu and C pl, for larger-the-better and smaller-the-better quality type respec tively proposed by Kane, are quoted and combined to propose a new index to evalu ate the quality of multiple characteristics of prestressing strand in this paper . Then, the principle of statistics is used to derive the one-to-one mathemati cal relationship of this new index and ratio of tallied. Finally, the procedure and criteria to evaluate the quality of prestressing strand is proposed. This in tegrated multi-quality property capability analysis model can be used to evalua te the multi-process capabilities and provide continuous improvement on manufac turing process of prestressing strand.展开更多
Low Earth orbit(LEO)satellite networks exhibit distinct characteristics,e.g.,limited resources of individual satellite nodes and dynamic network topology,which have brought many challenges for routing algorithms.To sa...Low Earth orbit(LEO)satellite networks exhibit distinct characteristics,e.g.,limited resources of individual satellite nodes and dynamic network topology,which have brought many challenges for routing algorithms.To satisfy quality of service(QoS)requirements of various users,it is critical to research efficient routing strategies to fully utilize satellite resources.This paper proposes a multi-QoS information optimized routing algorithm based on reinforcement learning for LEO satellite networks,which guarantees high level assurance demand services to be prioritized under limited satellite resources while considering the load balancing performance of the satellite networks for low level assurance demand services to ensure the full and effective utilization of satellite resources.An auxiliary path search algorithm is proposed to accelerate the convergence of satellite routing algorithm.Simulation results show that the generated routing strategy can timely process and fully meet the QoS demands of high assurance services while effectively improving the load balancing performance of the link.展开更多
The rise of multi-cloud systems has been spurred.For safety-critical missions,it is important to guarantee their security and reliability.To address trust constraints in a heterogeneous multi-cloud environment,this wo...The rise of multi-cloud systems has been spurred.For safety-critical missions,it is important to guarantee their security and reliability.To address trust constraints in a heterogeneous multi-cloud environment,this work proposes a novel scheduling method called matching and multi-round allocation(MMA)to optimize the makespan and total cost for all submitted tasks subject to security and reliability constraints.The method is divided into two phases for task scheduling.The first phase is to find the best matching candidate resources for the tasks to meet their preferential demands including performance,security,and reliability in a multi-cloud environment;the second one iteratively performs multiple rounds of re-allocating to optimize tasks execution time and cost by minimizing the variance of the estimated completion time.The proposed algorithm,the modified cuckoo search(MCS),hybrid chaotic particle search(HCPS),modified artificial bee colony(MABC),max-min,and min-min algorithms are implemented in CloudSim to create simulations.The simulations and experimental results show that our proposed method achieves shorter makespan,lower cost,higher resource utilization,and better trade-off between time and economic cost.It is more stable and efficient.展开更多
Hazardous wastes pose increasing threats to people and environment during the processes of offsite collection,storage,treatment,and disposal.A novel game theoretic model,including two levels,is developed for the corre...Hazardous wastes pose increasing threats to people and environment during the processes of offsite collection,storage,treatment,and disposal.A novel game theoretic model,including two levels,is developed for the corresponding optimization of emergency logistics,where the upper level indicates the location and capacity problem for the regulator,and the lower level reflects the allocation problem for the emergency commander.Different from other works in the literature,we focus on the issue of multi-quality coverages (full and partial coverages) in the optimization of facility location and allocation.To be specific,the regulator decides the location plan and the corresponding capacity of storing emergency groups for multiple types of hazmats,so to minimizes the total potential environmental risk posed by incident sites;while the commander minimizes the total costs to provide an efficient allocation policy.To solve the bi-level programming model,two solution techniques,namely a KKT condition approach and a heuristic model,are designed and compared.The proposed model and solution techniques are then applied to a hypothetical case and a real-world case to demonstrate the practicality and provide managerial insights.展开更多
文摘Prestressed concrete structures are main conformati on for the construction of high way bridges. The quality of prestressed concrete s tructures is mainly affected by the tensile strength of prestressing strand. In order to attain the purpose of economic design and long life span of prestressin g strand, the less relaxation property of strand type is suitable for constructi on and usage. Thus, the research and development of prestressing strand is requi red to reach the goals of high tensile strength and low relaxation. To ensure th e required quality of prestressing strand, the strand pull test and long period relaxation test are two important items for the quality assurance. There are thr ee specific items of the tensile strength test are belong to larger-the-better quality type. The quality type of smaller-the-better is for the long period r elaxation test. However, many existing methods are able to measure process capab ility for product with single quality characteristic and cannot be applied to mo st products with multiple properties. Thus, the indices of C pu and C pl, for larger-the-better and smaller-the-better quality type respec tively proposed by Kane, are quoted and combined to propose a new index to evalu ate the quality of multiple characteristics of prestressing strand in this paper . Then, the principle of statistics is used to derive the one-to-one mathemati cal relationship of this new index and ratio of tallied. Finally, the procedure and criteria to evaluate the quality of prestressing strand is proposed. This in tegrated multi-quality property capability analysis model can be used to evalua te the multi-process capabilities and provide continuous improvement on manufac turing process of prestressing strand.
基金National Key Research and Development Program(2021YFB2900604)。
文摘Low Earth orbit(LEO)satellite networks exhibit distinct characteristics,e.g.,limited resources of individual satellite nodes and dynamic network topology,which have brought many challenges for routing algorithms.To satisfy quality of service(QoS)requirements of various users,it is critical to research efficient routing strategies to fully utilize satellite resources.This paper proposes a multi-QoS information optimized routing algorithm based on reinforcement learning for LEO satellite networks,which guarantees high level assurance demand services to be prioritized under limited satellite resources while considering the load balancing performance of the satellite networks for low level assurance demand services to ensure the full and effective utilization of satellite resources.An auxiliary path search algorithm is proposed to accelerate the convergence of satellite routing algorithm.Simulation results show that the generated routing strategy can timely process and fully meet the QoS demands of high assurance services while effectively improving the load balancing performance of the link.
基金supported in part by the National Natural Science Foundation of China(61673123,61603100)in part by the Natural Science Foundation of Guangdong Province,China(2020A151501482)。
文摘The rise of multi-cloud systems has been spurred.For safety-critical missions,it is important to guarantee their security and reliability.To address trust constraints in a heterogeneous multi-cloud environment,this work proposes a novel scheduling method called matching and multi-round allocation(MMA)to optimize the makespan and total cost for all submitted tasks subject to security and reliability constraints.The method is divided into two phases for task scheduling.The first phase is to find the best matching candidate resources for the tasks to meet their preferential demands including performance,security,and reliability in a multi-cloud environment;the second one iteratively performs multiple rounds of re-allocating to optimize tasks execution time and cost by minimizing the variance of the estimated completion time.The proposed algorithm,the modified cuckoo search(MCS),hybrid chaotic particle search(HCPS),modified artificial bee colony(MABC),max-min,and min-min algorithms are implemented in CloudSim to create simulations.The simulations and experimental results show that our proposed method achieves shorter makespan,lower cost,higher resource utilization,and better trade-off between time and economic cost.It is more stable and efficient.
基金supported by grants from the National Natural Science Foundations of China under grant No.61803091the Natural Science Foundation of Guangdong province under grant No.2016A030310263as well as a Discovery Grant from the Natural Sciences and Engineering Research Council of Canada under grant No.RGPIN-2015-04013.
文摘Hazardous wastes pose increasing threats to people and environment during the processes of offsite collection,storage,treatment,and disposal.A novel game theoretic model,including two levels,is developed for the corresponding optimization of emergency logistics,where the upper level indicates the location and capacity problem for the regulator,and the lower level reflects the allocation problem for the emergency commander.Different from other works in the literature,we focus on the issue of multi-quality coverages (full and partial coverages) in the optimization of facility location and allocation.To be specific,the regulator decides the location plan and the corresponding capacity of storing emergency groups for multiple types of hazmats,so to minimizes the total potential environmental risk posed by incident sites;while the commander minimizes the total costs to provide an efficient allocation policy.To solve the bi-level programming model,two solution techniques,namely a KKT condition approach and a heuristic model,are designed and compared.The proposed model and solution techniques are then applied to a hypothetical case and a real-world case to demonstrate the practicality and provide managerial insights.
