Benefitting from UAVs’characteristics of flexible deployment and controllable movement in 3D space,odor source localization with multiple UAVs has been a hot research area in recent years.Considering the limited reso...Benefitting from UAVs’characteristics of flexible deployment and controllable movement in 3D space,odor source localization with multiple UAVs has been a hot research area in recent years.Considering the limited resources and insufficient battery capacities of UAVs,it is necessary to fast locate the odor source with low-complexity computation and minimal interaction under complicated environmental states.To this end,we propose a multi-UAV collaboration based odor source localization(MUC-OSL)method,where source estimation and UAV navigation are iteratively performed,aiming to accelerate the searching process and reduce the resource consumption of UAVs.Specifically,in the source estimation phase,we present a collaborative particle filter algorithm on the basis of UAVs’cognitive difference and collaborative information to improve source estimation accuracy.In the following navigation phase,an adaptive path planning algorithm is designed based on partially observable Markov decision process to distributedly determine the subsequent flying direction and moving steps of each UAV.The results of experiments conducted on two simulation platforms demonstrate that MUC-OSL outperforms existing efforts in terms of mean search time and success rate,and effectively reduces the resource consumption of UAVs.展开更多
We develop a quantum key distribution (QKD) system with fast active optical path length compensation. A rapid and reliable active optical path length compensation scheme is proposed and applied to a plug-and-play QKD ...We develop a quantum key distribution (QKD) system with fast active optical path length compensation. A rapid and reliable active optical path length compensation scheme is proposed and applied to a plug-and-play QKD system. The system monitors changes in key rates and controls it is own operation automatically. The system achieves its optimal performance within three seconds of operation, which includes a sifted key rate of 5.5 kbps and a quantum bit error rate of less than 2% after an abrupt temperature variation along the 25 km quantum channel. The system also operates well over a 24 h period while completing more than 60 active optical path length compensations.展开更多
Supply-demand allocation is important for supporting emergency food material management and decision making.This study proposed a supply-demand allocation method for market-supplied materials.The method considers the ...Supply-demand allocation is important for supporting emergency food material management and decision making.This study proposed a supply-demand allocation method for market-supplied materials.The method considers the constraint that market supply reserve depots(MSDs) need to preferentially supply emergency food materials to original demand points,which is mostly neglected in traditional methods.The constraint enables the method to provide a more rational allocation scheme of MSDs.Based on the supply-demand allocation method,an emergency material distribution path planning method under flood scenarios was further developed.Unlike the traditional methods,which mostly neglect simultaneous consideration of the travel time and path reliability factors,this method comprehensively achieves two critical objectives:the shortest path travel time and highest path reliability.The heuristic algorithms are used to solve the optimal path.It can enhance the safety and reliability of food material distributions.Three criteria-degree,squares clustering coefficient,and road design daily traffic volume-are integrated to evaluate the reliability of each road section based on the real road networks,and the impact of the flood on travel time is fully considered.A case study in Fengxian District,Shanghai,China,was conducted to demonstrate the feasibility of the method.Three categories of supplies-rice,drinking water,and infant milk-were chosen to represent the food supplies.The results of the case study can support decision making for emergency rescue and relief efforts of relevant government departments.The methods proposed provide methodological references for related studies in other similar regions.展开更多
For the optimization problem of the cold-chain emergency materials(CEM) distribution routes with multi-demand centers and soft time windows and to solve dispatching materials to medical treatment institutions in vario...For the optimization problem of the cold-chain emergency materials(CEM) distribution routes with multi-demand centers and soft time windows and to solve dispatching materials to medical treatment institutions in various places of the disaster areas under COVID-19, a multi-dimensional robust optimization(MRO) model was proposed, which was solved by a hybrid algorithm combined Pareto genetic algorithm and the improved grey relative analysis(IGRA). The proposed model comprehensively takes into consideration of the cost factors of the cold-chain logistics and robustness of solution with the purpose of minimizing the costs and maximizing robustness. The availability of the proposed approach and hybrid algorithm were thoroughly discussed and qualified through a real-world numerical simulation test case, which was a previous risk area located at Hubei Province. Research results show an average-cost reduction of 4.51% and a robustness increment of 11.69% in addition to consider the urgencies of demand. Consequently, not only the costs can be slightly reduced and the robustness be heightened, but also the blindness of the distribution can be avoided effectively with the demand urgency being considered. Research result indicates that when combining with the specific process of supplies dispatching in the prevention and control, the proposed approach is in a far better agreement in practice, and it could meet the diverse requirements of the emergency scenarios flexibly.展开更多
基金supported by National Natural Science Foundation of China(No.62072436 and No.62202449)National Key Research and Development Program of China(2021YFB2900102).
文摘Benefitting from UAVs’characteristics of flexible deployment and controllable movement in 3D space,odor source localization with multiple UAVs has been a hot research area in recent years.Considering the limited resources and insufficient battery capacities of UAVs,it is necessary to fast locate the odor source with low-complexity computation and minimal interaction under complicated environmental states.To this end,we propose a multi-UAV collaboration based odor source localization(MUC-OSL)method,where source estimation and UAV navigation are iteratively performed,aiming to accelerate the searching process and reduce the resource consumption of UAVs.Specifically,in the source estimation phase,we present a collaborative particle filter algorithm on the basis of UAVs’cognitive difference and collaborative information to improve source estimation accuracy.In the following navigation phase,an adaptive path planning algorithm is designed based on partially observable Markov decision process to distributedly determine the subsequent flying direction and moving steps of each UAV.The results of experiments conducted on two simulation platforms demonstrate that MUC-OSL outperforms existing efforts in terms of mean search time and success rate,and effectively reduces the resource consumption of UAVs.
基金was supported by the ICT R&D programs of Ministry of Science, ICT and Future Planning/Institute for Information & Communications Technology Promotion (Grant No. B0101-16-1355)the Korea Institute of Science and Technology research program (Grant No. 2E27231)Korea Institute of Science and Technology-Electronics And Telecommunications Research Institute research program (Grant No. 2V05340)
文摘We develop a quantum key distribution (QKD) system with fast active optical path length compensation. A rapid and reliable active optical path length compensation scheme is proposed and applied to a plug-and-play QKD system. The system monitors changes in key rates and controls it is own operation automatically. The system achieves its optimal performance within three seconds of operation, which includes a sifted key rate of 5.5 kbps and a quantum bit error rate of less than 2% after an abrupt temperature variation along the 25 km quantum channel. The system also operates well over a 24 h period while completing more than 60 active optical path length compensations.
基金funded by the National Natural Science Foundation of China (Grant Nos. 72074151, 42101314, and 42171282)supported by the Yangtze River Delta Urban Wetland Ecosystem National Field Scientific Observation and Research Station, Shanghai, China
文摘Supply-demand allocation is important for supporting emergency food material management and decision making.This study proposed a supply-demand allocation method for market-supplied materials.The method considers the constraint that market supply reserve depots(MSDs) need to preferentially supply emergency food materials to original demand points,which is mostly neglected in traditional methods.The constraint enables the method to provide a more rational allocation scheme of MSDs.Based on the supply-demand allocation method,an emergency material distribution path planning method under flood scenarios was further developed.Unlike the traditional methods,which mostly neglect simultaneous consideration of the travel time and path reliability factors,this method comprehensively achieves two critical objectives:the shortest path travel time and highest path reliability.The heuristic algorithms are used to solve the optimal path.It can enhance the safety and reliability of food material distributions.Three criteria-degree,squares clustering coefficient,and road design daily traffic volume-are integrated to evaluate the reliability of each road section based on the real road networks,and the impact of the flood on travel time is fully considered.A case study in Fengxian District,Shanghai,China,was conducted to demonstrate the feasibility of the method.Three categories of supplies-rice,drinking water,and infant milk-were chosen to represent the food supplies.The results of the case study can support decision making for emergency rescue and relief efforts of relevant government departments.The methods proposed provide methodological references for related studies in other similar regions.
基金supported by the National Natural Science Foundation of China (No.52062027,71861023 and 52002282)the "Double-first Class" Major Research Programs,Educational Department of Gansu Province (No.GSSYLXM-04)+1 种基金supported by the Natural Science Foundation of Zhejiang Province (LY21E080010)Philosophy and Social Science Foundation of Zhejiang Province (No.21NDJC163YB,22NDJC166YB)。
文摘For the optimization problem of the cold-chain emergency materials(CEM) distribution routes with multi-demand centers and soft time windows and to solve dispatching materials to medical treatment institutions in various places of the disaster areas under COVID-19, a multi-dimensional robust optimization(MRO) model was proposed, which was solved by a hybrid algorithm combined Pareto genetic algorithm and the improved grey relative analysis(IGRA). The proposed model comprehensively takes into consideration of the cost factors of the cold-chain logistics and robustness of solution with the purpose of minimizing the costs and maximizing robustness. The availability of the proposed approach and hybrid algorithm were thoroughly discussed and qualified through a real-world numerical simulation test case, which was a previous risk area located at Hubei Province. Research results show an average-cost reduction of 4.51% and a robustness increment of 11.69% in addition to consider the urgencies of demand. Consequently, not only the costs can be slightly reduced and the robustness be heightened, but also the blindness of the distribution can be avoided effectively with the demand urgency being considered. Research result indicates that when combining with the specific process of supplies dispatching in the prevention and control, the proposed approach is in a far better agreement in practice, and it could meet the diverse requirements of the emergency scenarios flexibly.
