Seismic anisotropy provides important constraints on deformation patterns of Earth＇s material. Rayleigh wave dispersion data with azimuthal anisotropy can be used to invert for depth-dependent shear wavespeed azimuth...Seismic anisotropy provides important constraints on deformation patterns of Earth＇s material. Rayleigh wave dispersion data with azimuthal anisotropy can be used to invert for depth-dependent shear wavespeed azimuthal anisotropy, therefore reflecting depth-varying deformation patterns in the crust and upper mantle. In this study, we propose a two-step method that uses the Neighborhood Algorithm （NA） for the point-wise inversion of depth-dependent shear wavespeeds and azimuthal anisotropy from Rayleigh wave azimuthally anisotropic dispersion data. The first step employs the NA to estimate depth- dependent Vsv （or the elastic parameter L） as well as their uncertainties from the isotropic part Rayleigh wave dispersion data. In the second step, we first adopt a difference scheme to compute approximate Rayleigh-wave phase velocity sensitivity kernels to azimuthally anisotropic parameters with respect to the velocity model obtained in the first step. Then we perform the NA to estimate the azimuthally anisotropic parameters Gc/L and Gs/L at depths separately from the corresponding cosine and sine terms of the azimuthally anisotropic dispersion data. Finally, we compute the depth-dependent magnitude and fast polariza- tion azimuth of shear wavespeed azimuthal anisotropy. The use of the global search NA and Bayesian analysis allows for more reliable estimates of depth-dependent shear wavespeeds and azimuthal anisotropy as well as their uncertainties.We illustrate the inversion method using the azimuthally anisotropic dispersion data in SE Tibet, where we find apparent changes of fast axes of shear wavespeed azimuthal anisotropy between the crust and uppermost mantle.展开更多
This paper presents a parallel composite local search algorithm based on multiple search neighborhoods to solve a special kind of timetable problem. The new algorithm can also effectively solve those problems that can...This paper presents a parallel composite local search algorithm based on multiple search neighborhoods to solve a special kind of timetable problem. The new algorithm can also effectively solve those problems that can be solved by general local search algorithms. Experimental results show that the new algorithm can generate better solutions than general local search algorithms.展开更多
Airports around the world commonly face challenges in managing airport slot allocation.Effective management of limited slot resources by civil aviation authority often requires redistributing requested slots among air...Airports around the world commonly face challenges in managing airport slot allocation.Effective management of limited slot resources by civil aviation authority often requires redistributing requested slots among airlines.The allocation process must operate within the prescribed capacity limits of the airport while adhering to established priorities and regulations.Additionally,ensuring market fairness is a key objective,as the value of airport slots plays a significant role in the adjustment process.This transforms the traditional time-shift-based problem into a complex multi-objective optimization problem.Addressing such complications is of significant importance to airlines,airports,and passengers alike.Due to the complexity of fairness metrics,traditional integer programming models encounter difficulties in finding effective solutions.This study proposes a neighborhood search strategy to tackle the single airport slot allocation,making it adaptable to both static and rolling capacity scenarios.Two Genetic Algorithms(GAs)are introduced,corresponding to time adjustment and sequence adjustment strategies,respectively.The GA based on the time adjustment strategy demonstrates high robustness,while the sequence adjustment strategy builds upon this GA to develop a simple heuristic algorithm that offers rapid convergence.Case studies conducted at seven airports in China confirm that all three algorithms yield high-quality adjustment solutions suitable for the majority of applications.Further,Pareto analysis reveals that these algorithms effectively balance the adjustment shifts and fairness metrics,demonstrating high practical value and broad applicability.展开更多
基金supported by National Natural Science Foundation of China (Grant number 41222028)China National Special Fund for Earthquake Scientific Research in Public Interest (Grant number 201508008)the Fundamental Research Funds for the Central Universities (WK2080000053)
文摘Seismic anisotropy provides important constraints on deformation patterns of Earth＇s material. Rayleigh wave dispersion data with azimuthal anisotropy can be used to invert for depth-dependent shear wavespeed azimuthal anisotropy, therefore reflecting depth-varying deformation patterns in the crust and upper mantle. In this study, we propose a two-step method that uses the Neighborhood Algorithm （NA） for the point-wise inversion of depth-dependent shear wavespeeds and azimuthal anisotropy from Rayleigh wave azimuthally anisotropic dispersion data. The first step employs the NA to estimate depth- dependent Vsv （or the elastic parameter L） as well as their uncertainties from the isotropic part Rayleigh wave dispersion data. In the second step, we first adopt a difference scheme to compute approximate Rayleigh-wave phase velocity sensitivity kernels to azimuthally anisotropic parameters with respect to the velocity model obtained in the first step. Then we perform the NA to estimate the azimuthally anisotropic parameters Gc/L and Gs/L at depths separately from the corresponding cosine and sine terms of the azimuthally anisotropic dispersion data. Finally, we compute the depth-dependent magnitude and fast polariza- tion azimuth of shear wavespeed azimuthal anisotropy. The use of the global search NA and Bayesian analysis allows for more reliable estimates of depth-dependent shear wavespeeds and azimuthal anisotropy as well as their uncertainties.We illustrate the inversion method using the azimuthally anisotropic dispersion data in SE Tibet, where we find apparent changes of fast axes of shear wavespeed azimuthal anisotropy between the crust and uppermost mantle.
文摘This paper presents a parallel composite local search algorithm based on multiple search neighborhoods to solve a special kind of timetable problem. The new algorithm can also effectively solve those problems that can be solved by general local search algorithms. Experimental results show that the new algorithm can generate better solutions than general local search algorithms.
基金supported in part by the National Natural Science Foundation of China(Nos.62167003,52302421)in part by the Diversified Investment Fund of Tianjin,China(No.23JCQNJC00210)。
文摘Airports around the world commonly face challenges in managing airport slot allocation.Effective management of limited slot resources by civil aviation authority often requires redistributing requested slots among airlines.The allocation process must operate within the prescribed capacity limits of the airport while adhering to established priorities and regulations.Additionally,ensuring market fairness is a key objective,as the value of airport slots plays a significant role in the adjustment process.This transforms the traditional time-shift-based problem into a complex multi-objective optimization problem.Addressing such complications is of significant importance to airlines,airports,and passengers alike.Due to the complexity of fairness metrics,traditional integer programming models encounter difficulties in finding effective solutions.This study proposes a neighborhood search strategy to tackle the single airport slot allocation,making it adaptable to both static and rolling capacity scenarios.Two Genetic Algorithms(GAs)are introduced,corresponding to time adjustment and sequence adjustment strategies,respectively.The GA based on the time adjustment strategy demonstrates high robustness,while the sequence adjustment strategy builds upon this GA to develop a simple heuristic algorithm that offers rapid convergence.Case studies conducted at seven airports in China confirm that all three algorithms yield high-quality adjustment solutions suitable for the majority of applications.Further,Pareto analysis reveals that these algorithms effectively balance the adjustment shifts and fairness metrics,demonstrating high practical value and broad applicability.
