Safe and efficient sortie scheduling on the confined flight deck is crucial for maintaining high combat effectiveness of the aircraft carrier.The primary difficulty exactly lies in the spatiotemporal coordination,i.e....Safe and efficient sortie scheduling on the confined flight deck is crucial for maintaining high combat effectiveness of the aircraft carrier.The primary difficulty exactly lies in the spatiotemporal coordination,i.e.,allocation of limited supporting resources and collision-avoidance between heterogeneous dispatch entities.In this paper,the problem is investigated in the perspective of hybrid flow-shop scheduling problem by synthesizing the precedence,space and resource constraints.Specifically,eight processing procedures are abstracted,where tractors,preparing spots,catapults,and launching are virtualized as machines.By analyzing the constraints in sortie scheduling,a mixed-integer planning model is constructed.In particular,the constraint on preparing spot occupancy is improved to further enhance the sortie efficiency.The basic trajectory library for each dispatch entity is generated and a delayed strategy is integrated to address the collision-avoidance issue.To efficiently solve the formulated HFSP,which is essentially a combinatorial problem with tightly coupled constraints,a chaos-initialized genetic algorithm is developed.The solution framework is validated by the simulation environment referring to the Fort-class carrier,exhibiting higher sortie efficiency when compared to existing strategies.And animation of the simulation results is available at www.bilibili.com/video/BV14t421A7Tt/.The study presents a promising supporting technique for autonomous flight deck operation in the foreseeable future,and can be easily extended to other supporting scenarios,e.g.,ammunition delivery and aircraft maintenance.展开更多
Recovery is a crucial supporting process for carrier aircraft,where a reasonable landing scheduling is expected to guide the fleet landing safely and quickly.Currently,there is little research on this topic,and most o...Recovery is a crucial supporting process for carrier aircraft,where a reasonable landing scheduling is expected to guide the fleet landing safely and quickly.Currently,there is little research on this topic,and most of it neglects potential influence factors,leaving the corresponding supporting efficiency questionable.In this paper,we study the landing scheduling problem for carrier aircraft considering the effects of bolting and aerial refueling.Based on the analysis of recovery mode involving the above factors,two types of primary constraints(i.e.,fuel constraint and wake interval constraint)are first described.Then,taking the landing sequencing as decision variables,a combinatorial optimization model with a compound objective function is formulated.Aiming at an efficient solution,an improved firefly algorithm is designed by integrating multiple evolutionary operators.In addition,a dynamic replanning mechanism is introduced to deal with special situations(i.e.,the occurrence of bolting and fuel shortage),where the high efficiency of the designed algorithm facilitates the online scheduling adjustment within seconds.Finally,numerical simulations with sufficient and insufficient fuel cases are both carried out,highlighting the necessity to consider bolting and aerial refueling during the planning procedure.Simulation results reveal that a higher bolting probability,as well as extra aerial refueling operations caused by fuel shortage,will lead to longer recovery complete time.Meanwhile,due to the strong optimum-seeking capability and solution efficiency of the improved algorithm,adaptive scheduling can be generated within milliseconds to deal with special situations,significantly improving the safety and efficiency of the recovery process.An animation is accessible at bilibili.com/video/BV1QprKY2EwD.展开更多
Combat effectiveness of unmanned aerial vehicle(UAV)formations can be severely affected by the mission execution reliability.During the practical execution phase,there are inevitable risks where UAVs being destroyed o...Combat effectiveness of unmanned aerial vehicle(UAV)formations can be severely affected by the mission execution reliability.During the practical execution phase,there are inevitable risks where UAVs being destroyed or targets failed to be executed.To improve the mission reliability,a resilient mission planning framework integrates task pre-and re-assignment modules is developed in this paper.In the task pre-assignment phase,to guarantee the mission reliability,probability constraints regarding the minimum mission success rate are imposed to establish a multi-objective optimization model.And an improved genetic algorithm with the multi-population mechanism and specifically designed evolutionary operators is used for efficient solution.As in the task-reassignment phase,possible trigger events are first analyzed.A real-time contract net protocol-based algorithm is then proposed to address the corresponding emergency scenario.And the dual objective used in the former phase is adapted into a single objective to keep a consistent combat intention.Three cases of different scales demonstrate that the two modules cooperate well with each other.On the one hand,the pre-assignment module can generate high-reliability mission schedules as an elaborate mathematical model is introduced.On the other hand,the re-assignment module can efficiently respond to various emergencies and adjust the original schedule within a millisecond.The corresponding animation is accessible at bilibili.com/video/BV12t421w7EE for better illustration.展开更多
基金the financial support of the National Key Research and Development Plan(2021YFB3302501)the financial support of the National Natural Science Foundation of China(12102077)。
文摘Safe and efficient sortie scheduling on the confined flight deck is crucial for maintaining high combat effectiveness of the aircraft carrier.The primary difficulty exactly lies in the spatiotemporal coordination,i.e.,allocation of limited supporting resources and collision-avoidance between heterogeneous dispatch entities.In this paper,the problem is investigated in the perspective of hybrid flow-shop scheduling problem by synthesizing the precedence,space and resource constraints.Specifically,eight processing procedures are abstracted,where tractors,preparing spots,catapults,and launching are virtualized as machines.By analyzing the constraints in sortie scheduling,a mixed-integer planning model is constructed.In particular,the constraint on preparing spot occupancy is improved to further enhance the sortie efficiency.The basic trajectory library for each dispatch entity is generated and a delayed strategy is integrated to address the collision-avoidance issue.To efficiently solve the formulated HFSP,which is essentially a combinatorial problem with tightly coupled constraints,a chaos-initialized genetic algorithm is developed.The solution framework is validated by the simulation environment referring to the Fort-class carrier,exhibiting higher sortie efficiency when compared to existing strategies.And animation of the simulation results is available at www.bilibili.com/video/BV14t421A7Tt/.The study presents a promising supporting technique for autonomous flight deck operation in the foreseeable future,and can be easily extended to other supporting scenarios,e.g.,ammunition delivery and aircraft maintenance.
基金the financial support of the National Natural Science Foundation of China(12102077,12161076)the Natural Science and Technology Program of Liaoning Province(2023-BS-061).
文摘Recovery is a crucial supporting process for carrier aircraft,where a reasonable landing scheduling is expected to guide the fleet landing safely and quickly.Currently,there is little research on this topic,and most of it neglects potential influence factors,leaving the corresponding supporting efficiency questionable.In this paper,we study the landing scheduling problem for carrier aircraft considering the effects of bolting and aerial refueling.Based on the analysis of recovery mode involving the above factors,two types of primary constraints(i.e.,fuel constraint and wake interval constraint)are first described.Then,taking the landing sequencing as decision variables,a combinatorial optimization model with a compound objective function is formulated.Aiming at an efficient solution,an improved firefly algorithm is designed by integrating multiple evolutionary operators.In addition,a dynamic replanning mechanism is introduced to deal with special situations(i.e.,the occurrence of bolting and fuel shortage),where the high efficiency of the designed algorithm facilitates the online scheduling adjustment within seconds.Finally,numerical simulations with sufficient and insufficient fuel cases are both carried out,highlighting the necessity to consider bolting and aerial refueling during the planning procedure.Simulation results reveal that a higher bolting probability,as well as extra aerial refueling operations caused by fuel shortage,will lead to longer recovery complete time.Meanwhile,due to the strong optimum-seeking capability and solution efficiency of the improved algorithm,adaptive scheduling can be generated within milliseconds to deal with special situations,significantly improving the safety and efficiency of the recovery process.An animation is accessible at bilibili.com/video/BV1QprKY2EwD.
基金supported by the National Key Research and Development Plan(Grant No.2021YFB3302501)the National Natural Science Foundation of China(Grant Nos.12102077,12161076,U2241263).
文摘Combat effectiveness of unmanned aerial vehicle(UAV)formations can be severely affected by the mission execution reliability.During the practical execution phase,there are inevitable risks where UAVs being destroyed or targets failed to be executed.To improve the mission reliability,a resilient mission planning framework integrates task pre-and re-assignment modules is developed in this paper.In the task pre-assignment phase,to guarantee the mission reliability,probability constraints regarding the minimum mission success rate are imposed to establish a multi-objective optimization model.And an improved genetic algorithm with the multi-population mechanism and specifically designed evolutionary operators is used for efficient solution.As in the task-reassignment phase,possible trigger events are first analyzed.A real-time contract net protocol-based algorithm is then proposed to address the corresponding emergency scenario.And the dual objective used in the former phase is adapted into a single objective to keep a consistent combat intention.Three cases of different scales demonstrate that the two modules cooperate well with each other.On the one hand,the pre-assignment module can generate high-reliability mission schedules as an elaborate mathematical model is introduced.On the other hand,the re-assignment module can efficiently respond to various emergencies and adjust the original schedule within a millisecond.The corresponding animation is accessible at bilibili.com/video/BV12t421w7EE for better illustration.
