In this paper, we consider a hyper-exponential jump-diffusion model with a constant dividend barrier. Explicit solutions for the Laplace transform of the ruin time, and the Gerber- Shiu function are obtained via marti...In this paper, we consider a hyper-exponential jump-diffusion model with a constant dividend barrier. Explicit solutions for the Laplace transform of the ruin time, and the Gerber- Shiu function are obtained via martingale stopping.展开更多
This paper proposes an enhanced arithmetic optimization algorithm(AOA)called PSAOA that incorporates the proposed probabilistic search strategy to increase the searching quality of the original AOA.Furthermore,an adju...This paper proposes an enhanced arithmetic optimization algorithm(AOA)called PSAOA that incorporates the proposed probabilistic search strategy to increase the searching quality of the original AOA.Furthermore,an adjustable parameter is also developed to balance the exploration and exploitation operations.In addition,a jump mechanism is included in the PSAOAto assist individuals in jumping out of local optima.Using 29 classical benchmark functions,the proposed PSAOA is extensively tested.Compared to the AOA and other well-known methods,the experiments demonstrated that the proposed PSAOA beats existing comparison algorithms on the majority of the test functions.展开更多
目的化工园区救援机器人的路径规划是目前研究的热点,针对救援机器人在路径规划中使用传统A^(*)算法存在遍历冗余节点、内存消耗较大和运算速度较慢的问题,提出一种改进的A^(*)算法。方法设计了自适应权重评价函数,用于动态调整实际代价...目的化工园区救援机器人的路径规划是目前研究的热点,针对救援机器人在路径规划中使用传统A^(*)算法存在遍历冗余节点、内存消耗较大和运算速度较慢的问题,提出一种改进的A^(*)算法。方法设计了自适应权重评价函数,用于动态调整实际代价,以提升算法的效率与收敛速度;采用跳点搜索策略(Jump Point Search,JPS)来筛选跳点,降低内存消耗和节点估计;运用三次均匀B样条曲线对优化后的路径进行处理,提高救援机器人前进的稳定性和可行性。结果通过构建化工园区Unity3D仿真场景,对救援机器人路径规划问题进行仿真研究,仿真结果表明:改进后的A^(*)算法展现出较高的效率及准确性。结论该算法为化工园区救援机器人的路径规划提供了一种更高效、更智能的解决方案,满足化工园区路径快速规划的需求。展开更多
基金Supported by the Natural Science Foundation of Jiangsu Province(BK20130260)the National Natural Science Foundation of China(11301369)the Postdoctoral Science Foundation of China(2013M540371)
文摘In this paper, we consider a hyper-exponential jump-diffusion model with a constant dividend barrier. Explicit solutions for the Laplace transform of the ruin time, and the Gerber- Shiu function are obtained via martingale stopping.
基金partially supported by the Fundamental Research Funds for the Central Universities(WUT:2022IVA067)the National Natural Science Foundation of China(Grant No.:72172112)the Fundamental Research Funds for the Central Universities(HUST:2019kfyRCPY038).
文摘This paper proposes an enhanced arithmetic optimization algorithm(AOA)called PSAOA that incorporates the proposed probabilistic search strategy to increase the searching quality of the original AOA.Furthermore,an adjustable parameter is also developed to balance the exploration and exploitation operations.In addition,a jump mechanism is included in the PSAOAto assist individuals in jumping out of local optima.Using 29 classical benchmark functions,the proposed PSAOA is extensively tested.Compared to the AOA and other well-known methods,the experiments demonstrated that the proposed PSAOA beats existing comparison algorithms on the majority of the test functions.
文摘目的化工园区救援机器人的路径规划是目前研究的热点,针对救援机器人在路径规划中使用传统A^(*)算法存在遍历冗余节点、内存消耗较大和运算速度较慢的问题,提出一种改进的A^(*)算法。方法设计了自适应权重评价函数,用于动态调整实际代价,以提升算法的效率与收敛速度;采用跳点搜索策略(Jump Point Search,JPS)来筛选跳点,降低内存消耗和节点估计;运用三次均匀B样条曲线对优化后的路径进行处理,提高救援机器人前进的稳定性和可行性。结果通过构建化工园区Unity3D仿真场景,对救援机器人路径规划问题进行仿真研究,仿真结果表明:改进后的A^(*)算法展现出较高的效率及准确性。结论该算法为化工园区救援机器人的路径规划提供了一种更高效、更智能的解决方案,满足化工园区路径快速规划的需求。
