基于虚拟力的无线传感器网络覆盖算法易陷入局部最优,导致覆盖率低、收敛速度慢。针对上述问题,提出一种基于虚拟力和泰森多边形划分的分布式覆盖(virtual force Voronoi partition,VFVP)优化算法。通过虚拟力方案尽可能分散节点,提高...基于虚拟力的无线传感器网络覆盖算法易陷入局部最优,导致覆盖率低、收敛速度慢。针对上述问题,提出一种基于虚拟力和泰森多边形划分的分布式覆盖(virtual force Voronoi partition,VFVP)优化算法。通过虚拟力方案尽可能分散节点,提高监测区域的覆盖率,采用集合划分泰森多边形方案和Minmax算法减少虚拟力末端中覆盖率下降的情况,使用质心算法提高虚拟力算法的收敛速度。相比基于虚拟力的网络覆盖算法,VFVP算法提高了5%左右的覆盖率。展开更多
This paper investigates the application of the Nash equilibrium solution method within 2-versus-1 impulsive orbital pursuit–evasion(P-E)scenarios,involving 2 pursuers and an evader.Through the integration of game the...This paper investigates the application of the Nash equilibrium solution method within 2-versus-1 impulsive orbital pursuit–evasion(P-E)scenarios,involving 2 pursuers and an evader.Through the integration of game theory and coordinated strategies between the pursuers,the initial 2-pursuer 1-evader game((P_(1),P_(2))-E)is transformed into a composite 1-pursuer 1-evader game(P_(2)-(P_(1)-E)).To address the core challenge of the P-E game,we utilize the MinMax bilateral optimization algorithm to determine optimal strategies in each game iteration,ensuring fairness and equal opportunities for all involved parties.Within the composite P-E framework,the second pursuer(P_(2))assumes responsibility for executing a coordinated pursuit strategy,including the evaluation and tracking of the anticipated outcome of P_(1)−E.Subsequently,the evader formulates an optimal counterplay by reverse engineering the potential role assignments and strategies of the pursuers.In order to explore the intricate aspects of these scenarios,our study harnesses Monte Carlo statistical methods,offering insights into critical factors such as initial positions,impulse intervals,and magnitudes of delta-V within orbital settings,all of which substantially influence game outcomes.Ultimately,this research not only advances our understanding of multiagent orbital P-E dynamics but also establishes a foundation for more informed and effective strategic planning in practical space missions.It aims to ensure mission success and responsible resource allocation in the domain of space exploration.展开更多
文摘基于虚拟力的无线传感器网络覆盖算法易陷入局部最优,导致覆盖率低、收敛速度慢。针对上述问题,提出一种基于虚拟力和泰森多边形划分的分布式覆盖(virtual force Voronoi partition,VFVP)优化算法。通过虚拟力方案尽可能分散节点,提高监测区域的覆盖率,采用集合划分泰森多边形方案和Minmax算法减少虚拟力末端中覆盖率下降的情况,使用质心算法提高虚拟力算法的收敛速度。相比基于虚拟力的网络覆盖算法,VFVP算法提高了5%左右的覆盖率。
基金supported by the National Key R&D Program of China:Gravitational Wave Detection Project(Nos.2021YFC22026,2021YFC2202601,2021YFC2202603)the National Natural Science Foundation of China(No.12172288).
文摘This paper investigates the application of the Nash equilibrium solution method within 2-versus-1 impulsive orbital pursuit–evasion(P-E)scenarios,involving 2 pursuers and an evader.Through the integration of game theory and coordinated strategies between the pursuers,the initial 2-pursuer 1-evader game((P_(1),P_(2))-E)is transformed into a composite 1-pursuer 1-evader game(P_(2)-(P_(1)-E)).To address the core challenge of the P-E game,we utilize the MinMax bilateral optimization algorithm to determine optimal strategies in each game iteration,ensuring fairness and equal opportunities for all involved parties.Within the composite P-E framework,the second pursuer(P_(2))assumes responsibility for executing a coordinated pursuit strategy,including the evaluation and tracking of the anticipated outcome of P_(1)−E.Subsequently,the evader formulates an optimal counterplay by reverse engineering the potential role assignments and strategies of the pursuers.In order to explore the intricate aspects of these scenarios,our study harnesses Monte Carlo statistical methods,offering insights into critical factors such as initial positions,impulse intervals,and magnitudes of delta-V within orbital settings,all of which substantially influence game outcomes.Ultimately,this research not only advances our understanding of multiagent orbital P-E dynamics but also establishes a foundation for more informed and effective strategic planning in practical space missions.It aims to ensure mission success and responsible resource allocation in the domain of space exploration.
