强迫非简谐振子随机行为研究

一个动力系统的状态依赖于其中的控制参数。许多描述保守或耗散系统的非线性方程,在一定的参数范围内表现出内在的随机性。本文就一类强迫非简谐振子出现随机行为问题作一些讨论并给出数值计算的结果。     

A survey on metaheuristics for stochastic combinatorial optimization

Metaheuristics are general algorithmic frameworks, often nature-inspired, designed to solve complex optimization problems, and they are a growing research area since a few decades. In recent years, metaheuristics are emerging as successful alternatives to more classical approaches also for solving optimization problems that include in their mathematical formulation uncertain, stochastic, and dynamic information. In this paper metaheuristics such as Ant Colony Optimization, Evolutionary Computation, Simulated Annealing, Tabu Search and others are introduced, and their applications to the class of Stochastic Combinatorial Optimization Problems (SCOPs) is thoroughly reviewed. Issues common to all metaheuristics, open problems, and possible directions of research are proposed and discussed. In this survey, the reader familiar to metaheuristics finds also pointers to classical algorithmic approaches to optimization under uncertainty, and useful informations to start working on this problem domain, while the reader new to metaheuristics should find a good tutorial in those metaheuristics that are currently being applied to optimization under uncertainty, and motivations for interest in this field.

Metabolic network modelling: Including stochastic effects

We propose to model the dynamics of metabolic networks from a systems biology point of view by four dynamical structure elements: potential function, translocation matrix, degradation matrix, and stochastic force. These four elements are balanced to determine the network dynamics, which gives arise to a special stochastic differential equation supplemented by a relationship between the stochastic force and the degradation matrix. Important network behaviors can be obtained from the potential function without explicitly solving for the time-dependent solution. The existence of such a potential function suggests a global optimization principle. The existence stochastic force corresponds naturally to the hierarchical structure in metabolic networks. We provide theoretical evidences to justify our proposal by discussing its connections to others large-scale biochemical systems approaches, such as the network thermodynamics theory, biochemical systems theory, metabolic control analysis, and flux balance analysis. Experimental data displaying stochasticity which carries important biological information are also pointed out.