最优指派问题匈牙利算法的探讨与C++实现

介绍了匈牙利算法的基本理论,并把这个理论通过实例应用到了最优指派问题的解决方案中,给出了可以实现该方法的C 程序。     

基于混合优化算法的带时间窗的车辆调度问题求解研究

论文建立了带时间窗的车辆调度问题的数学模型，并针对遗传算法在局部搜索能力方面的不足，提出将模拟退火算法与遗传算法相结合，从而构造了求解车辆调度问题的混合优化算法，并进行了实验计算。计算结果表明，用这种混合优化算法求解车辆调度问题，可以在一定程度上用模拟退火算法突跳性克服遗传算法在局部搜索能力方面的不足，从而得到质量较高的解。     

一种基于遗传算法求解车间调度问题的优化方法

遗传算法是解决车间调度问题的有效方法之一。但在构造适应度函数时由于调度问题诸多的束条件使得直接求解十分困难。罚函数法将约束条件加到目标函数上，变有约束为无约束．能较易求解该类问题。     

灰色预测算法在物流园区需求预测中的应用

对物流园区需求预测进行了系统分析,介绍了灰色预测算法,和物流园区腹地划分方法;结合连云港港口物流园区需求预测的实例进一步阐述了灰色预测算法在物流园区需求预测中的应用.     

一种基于佳点集遗传算法的物流配送网络优化

首先根据实际问题分析了物流配送网络优化模型的各个关键组成部分,包括优化目标、决策变量和约束条件,并针对目前物流配送网络优化算法中存在的一些问题提出了一种新的算法,其核心是佳点集遗传算法。该算法编码采用prufer num ber结构,变异和交叉概率自适应选择。     

地区综合实力的ANN分析

人工神经网络通过神经元之间的相互作用来完成整个网络的信息处理，具有自学习和自适应等一系列优点，因而用它来评价地区综合实力是可行的。针对地区综合实力评价问题，建立了基于神经网络的评价系统，给出了应用实例。     

Seasonality and Markov switching in an unobserved component time series model

It is generally acknowledged that the growth rate of output, the seasonal pattern, and the business cycle are best estimated simultaneously. To achieve this, we develop an unobserved component time series model for seasonally unadjusted US GDP. Our model incorporates a Markov switching regime to produce periods of expansion and recession, both of which are characterized by different underlying growth rates. Although both growth rates are time-varying, they are assumed to be cointegrated. The analysis is Bayesian, which fully accounts for all sources of uncertainty. Comparison with results from a similar model for seasonally adjusted data indicates that the seasonal adjustment of the data significantly alters several aspects of the full model. First Version Received: January 2001/Final Version Received: February 2002 Send offprint requests to: Rob Luginbuhl?Correspondence to: Rob Luginbuhl     

高校排课算法的设计

该文主要介绍了高校排课系统中排课算法的设计,通过在排课之前对要排课的数据进行优化处理,从而使得排课的冲突减少,提高了排课的效率。     

用神经网络对开式冷挤压极限变形程度的预测

给出了基于 BP网络的极限变形程度预测的分析方法 ,得到了开式冷挤压εmax神经网络计算结果 ,与实验结果比较 ,其精度较高 ,证明了神经网络模型在开式冷挤压工艺中应用的可行性。     

Genetic risk and value

A conceptual truth about risks is that they involve a possible and future adverse effect or a negative value of some kind. The genetic risks that individuals may face in the health care setting differ in some crucial respects to other kind of risks. The aims of this paper are to analyse the notion of value in the context of genetic risk in the setting of health care, and to suggest a conception of the evaluative aspect of genetic risk that is fruitful for genetic risk information. Two influential and relevant approaches to value, preferentialism and the capability approach, are discussed in the light of certain distinctive features of genetic risk and a third, a sensibility theory of value is suggested. According to this view, the concept of risk is a so-called ‘thick’ evaluative concept that has both a world-guiding function as well as an action-guiding or normative function. It is argued that this provides a more promising way to think about genetic risks in the clinical setting.