Aiming at the intervention decision-making problem in manned/unmanned aerial vehicle（MAV/UAV） cooperative engagement, this paper carries out a research on allocation strategy of emergency discretion based on human f...Aiming at the intervention decision-making problem in manned/unmanned aerial vehicle（MAV/UAV） cooperative engagement, this paper carries out a research on allocation strategy of emergency discretion based on human factors engineering（HFE）.Firstly, based on the brief review of research status of HFE, it gives structural description to emergency in the process of cooperative engagement and analyzes intervention of commanders. After that,constraint conditions of intervention decision-making of commanders based on HFE（IDMCBHFE） are given, and the mathematical model, which takes the overall efficiency value of handling emergencies as the objective function, is established. Then, through combining K-best and variable neighborhood search（VNS） algorithm, a K-best optimization variable neighborhood search mixed algorithm（KBOVNSMA） is designed to solve the model. Finally,through three groups of simulation experiments, effectiveness and superiority of the proposed algorithm are verified.展开更多
Social distancing during COVID-19 has become one of the most important measures in reducing the risks of the spread of the virus. Implementing thesemeasures at universities is crucial and directly related to the physi...Social distancing during COVID-19 has become one of the most important measures in reducing the risks of the spread of the virus. Implementing thesemeasures at universities is crucial and directly related to the physical attendance ofthe populations of students, professors, employees, and other members on campus. This research proposes an automated scheduling approach that can help universities and schools comply with the social distancing regulations by providingassistance in avoiding huge assemblages of people. Furthermore, this paper proposes a novel course timetable-scheduling scheme based on four main constraints.First, a distance of two meters must be maintained between each student inside theclassroom. Second, no classrooms should contain more than 20% of their regularcapacity. Third, there would be no back-to-back classes. Lastly, no lectures shouldbe held simultaneously in adjacent classrooms. The proposed approach wasimplemented using a variable neighborhood search (VNS) approach with an adaptive neighborhood structure (AD-NS) to resolve the problem of scheduling coursetimetables at Al-Ahlyyia Amman University. However, the experimental resultsshow that the proposed techniques outperformed the standard VNS tested on university course timetabling benchmark dataset ITC2007-Track3. Meanwhile, theapproach was tested using datasets collected from the faculty of information technology at Al-Ahlyyia Amman University (Jordan). Where the results showed that,the proposed technique could help educational institutes to resume their regularoperations while complying with the social distancing guidelines.展开更多
基金supported by the National Natural Science Foundation of China(61573017)the Doctoral Foundation of Air Force Engineering University(KGD08101604)
文摘Aiming at the intervention decision-making problem in manned/unmanned aerial vehicle（MAV/UAV） cooperative engagement, this paper carries out a research on allocation strategy of emergency discretion based on human factors engineering（HFE）.Firstly, based on the brief review of research status of HFE, it gives structural description to emergency in the process of cooperative engagement and analyzes intervention of commanders. After that,constraint conditions of intervention decision-making of commanders based on HFE（IDMCBHFE） are given, and the mathematical model, which takes the overall efficiency value of handling emergencies as the objective function, is established. Then, through combining K-best and variable neighborhood search（VNS） algorithm, a K-best optimization variable neighborhood search mixed algorithm（KBOVNSMA） is designed to solve the model. Finally,through three groups of simulation experiments, effectiveness and superiority of the proposed algorithm are verified.
文摘Social distancing during COVID-19 has become one of the most important measures in reducing the risks of the spread of the virus. Implementing thesemeasures at universities is crucial and directly related to the physical attendance ofthe populations of students, professors, employees, and other members on campus. This research proposes an automated scheduling approach that can help universities and schools comply with the social distancing regulations by providingassistance in avoiding huge assemblages of people. Furthermore, this paper proposes a novel course timetable-scheduling scheme based on four main constraints.First, a distance of two meters must be maintained between each student inside theclassroom. Second, no classrooms should contain more than 20% of their regularcapacity. Third, there would be no back-to-back classes. Lastly, no lectures shouldbe held simultaneously in adjacent classrooms. The proposed approach wasimplemented using a variable neighborhood search (VNS) approach with an adaptive neighborhood structure (AD-NS) to resolve the problem of scheduling coursetimetables at Al-Ahlyyia Amman University. However, the experimental resultsshow that the proposed techniques outperformed the standard VNS tested on university course timetabling benchmark dataset ITC2007-Track3. Meanwhile, theapproach was tested using datasets collected from the faculty of information technology at Al-Ahlyyia Amman University (Jordan). Where the results showed that,the proposed technique could help educational institutes to resume their regularoperations while complying with the social distancing guidelines.
