基于精英进化导向的多目标PID参数优化

在多目标优化问题中,决策者必须对Pareto前沿的众多非劣解做出选择.本文将决策偏好融入Pareto优化过程,提出一种基于精英导向机制的多目标遗传算法,根据决策偏好选择Pareto最优解为精英,利用无损有限精度法和归一增量距离保持种群多样性,通过多种群进化机制将决策偏好的影响传播到整个种群.该方法成功应用于自动导引车(AGV)伺服系统的PID参数优化,可根据决策偏好快速有效地定向搜索Pareto最优解,保证伺服控制达到路径跟踪要求的速度响应性能.     

不允许借贷的最优消费及资产决策模型研究

引入遗留财富重视程度因子,在无借贷约束和不允许借贷约束的条件下,建立了有穷时间限的最优消费与资产决策模型.运用随机最优控制理论及鞅最优性原理求出了模型的显式最优解.在此基础上,运用比较静态分析方法考察了在有约束和没有约束两种市场中的消费行为,并对两种市场中的消费和资产决策行为进行了比较研究.     

国际化创新人才的培养——从学生角度探讨

本文从当今中国人才竞争的状况和人才发展的严峻形势出发,在分析教育体制、学生能动性,以及未来可能的发展趋势基础上,阐述培养国际化创新性人才和构造全球化高等教育的必要性。结合教学实践与网络的知识对国际化创新人才进行结构化描述,最后,对如何培养创新性人才提出具体的方案,旨在为现阶段教育教学模式提供一些参考。     

多目标微粒群优化算法综述

作为一种有效的多目标优化工具,微粒群优化(PSO)算法已经得到广泛研究与认可.首先对多目标优化问题进行了形式化描述,介绍了微粒群优化算法与遗传算法的区别,并将多目标微粒群优化算法(MOPSO)分为以下几类:聚集函数法、基于目标函数排序法、子群法、基于Pareto支配算法和其他方法,分析了各类算法的主要思想、特点及其代表性算法.其次,针对非支配解的选择、外部档案集的修剪、解集多样性的保持以及微粒个体历史最优解和群体最优解的选取等热点问题进行了论述,并在此基础上对各类典型算法进行了比较.最后,根据当前MOPSO算法的研究状况,提出了该领域的发展方向.     

Existence results for impulsive differential inclusions with nonlocal conditions

In this paper, we shall establish sufficient conditions for the existence of mild solutions for nonlocal impulsive differential inclusions. On the basis of the fixed point theorems for multivalued maps and the technique of approximate solutions, new results are obtained. Examples are also provided to illustrate our results.     

New exact solutions for the KdV equation with higher order nonlinearity by using the variational method

The Korteweg-de Vries (KdV) equation with higher order nonlinearity models the wave propagation in one-dimensional nonlinear lattice. A higher-order extension of the familiar KdV equation is produced for internal solitary waves in a density and current stratified shear flow with a free surface. The variational approximation method is applied to obtain the solutions for the well-known KdV equation. Explicit solutions are presented and compared with the exact solutions. Very good agreement is achieved, demonstrating the high efficiency of variational approximation method. The existence of a Lagrangian and the invariant variational principle for the higher order KdV equation are discussed. The simplest version of the variational approximation, based on trial functions with two free parameters is demonstrated. The jost functions by quadratic, cubic and fourth order polynomials are approximated. Also, we choose the trial jost functions in the form of exponential and sinh solutions. All solutions are exact and stable, and have applications in physics.     

基于拥挤距离的动态粒子群多目标优化算法

提出了一种改进的基于拥挤距离的动态粒子群多目标优化算法。为提高粒子的全局搜索能力,提出了新的动态变化惯性权重和加速因子的方法。引进了拥挤距离排序方法维护外部精英集和更新全局最优值。为保持非劣解的多样性,采用了小概率变异机制,并根据种群的大小选择不同的变异概率。最后,把算法应用到5个典型的多目标测试函数并与其他算法进行比较。实验结果表明,该算法所得的Pareto解集有很好的收敛性和多样性。     

Distributed evolutionary multi-objective mesh-partitioning algorithm for parallel finite element computations

Majority of the mesh-partitioning algorithms attempt to optimise the interprocessor communications, while balancing the computational load among the processors. However, it is desirable to simultaneously optimise the submesh aspect ratios in order to significantly improve the convergence characteristics of the domain decomposition based Preconditioned-conjugate-gradient algorithms, being used extensively in the state-of-the-art parallel finite element codes. Keeping this in view, a new distributed multi-objective mesh-partitioning algorithm using evolutionary computing techniques is proposed in this paper. Effectiveness of the proposed distributed mesh-partitioning algorithm is demonstrated by solving several unstructured meshes of practical-engineering problems and also benchmark problems.