Synchronized Flow in a Cellular Automaton Model with Time Headway Dependent Randomization

We propose another possible mechanism of synchronized flow, i,e. that a time headway dependent randomization can exhibit synchronized flow. Based on this assumption, we present a new cellular automaton （CA） model for traffic flow, in which randomization effect is enhanced with the decrease of time headway. We study fundamental diagram and spatial-temporal diagrams of the model and perform microscopic analysis of time series data, which shows the model could reproduce synchronized flow as expected. It is also shown that a spontaneous transition from synchronized flow to jam could be observed by incorporating slow-to-start effect into the model. We expect that our work could contribute to the understanding of the real origin of synchronized flow.     

Phase transition in evolution of traffic flow with scale-free property

This paper investigates the behaviour of traffic flow in traffic systems with a new model based on the NaSch model and cluster approximation of mean-field theory. The proposed model aims at constructing a mapping relationship between the microcosmic behaviour and the macroscopic property of traffic flow. Results demonstrate that scale-free phenomenon of the evolution network becomes obvious when the density value of traffic flow reaches at the critical point of phase transition from free flow to traffic congestion, and jamming is limited in this scale-free structure.     

具有相容子问题的序列二次规划新算法

借助ε-约束集与一种特殊的罚函数,给出了一个具有相容子问题的序列二次规划新算法,较圆满地解决了SQP算法中的相容性问题,并证明了该算法仍保持全局收敛和超线性收敛的性质.     

A SUPERMEMORY GRADIENT PROJECTION ALGORITHM FOR OPTIMIZATION PROBLEM WITH NONLINEAR CONSTRAINTS

In this paper, by extending concept of the supermemory gradient method for unconstrainedoptimization problems, we present a supermemory gradient projection algorithm for nonlinearprograrnming with nonlinear constraints. Under some suitable conditions we prove its globalconvergence.     

非线性约束条件下一个超线性收敛的可行方法

在本文中，我们对非线性不等式约束条件下的非线性优化问题给出了一个新的ＳＱＰ类可行方法．此算法不但结构简单、易于计算，并且在适当的假设条件下，我们证明了算法具有全局收敛性及超线性收敛性     

双层线性规划的一个全局优化方法

用线性规划对偶理论分析了双层线性规划的最优解与下层问题的对偶问题可行域上极点之间的关系，通过求得下层问题的对偶问题可行域上的极点，将双层线性规划转化为有限个线性规划问题，从而用线性规划方法求得问题的全局最优解．由于下层对偶问题可行域上只有有限个极点，所以方法具有全局收敛性．