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。     

Matching and anonymity

This work introduces a set-theoretic foundation of deterministic bilateral matching processes and studies their properties. In particular, it formalizes a link between matching and informational constraints by developing a notion of anonymity that is based on the agents’ matching histories. It also explains why and how various matching processes generate different degrees of “informational isolation” in the economy. We illustrate the usefulness of our approach to modeling matching frameworks by discussing the classical turnpike model of Townsend.This research is supported in part by the NSF grants EIA-0075506, SES-0128039, DMS-0437210, and ACI-0325846. We thank two anonymous referees for constructive comments that improved the exposition of the paper. We also thank the participants in seminars at the University of Aarhus, Purdue University, University of Texas at Austin, and at the XI Meeting on Real Analysis and Measure Theory in 2004, the spring 2004 Midwest Economic Theory Meeting, the summer 2004 North American and European Econometric Society meetings.     

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。     

Revenue Sharing versus Expenditure Sharing in a Federal System

Problems of intergovernmental policy coordination can take many forms and are becoming increasingly important with continuing economic integration. In this paper we focus on the fiscal competition problem where the non-cooperative choice of taxes and transfers among governments typically leads to a suboptimal outcome. We look at the effect of two widely used corrective policies: revenue sharing and expenditure sharing (or intergovernmental matching grants). Our main result is that these two corrective policies have opposite effects depending on the form of competition between governments, namely whether governments compete in taxes or expenditures. More precisely, for any form of competition, revenue sharing is desirable exactly when expenditure sharing is not and vice versa. The implication is that the choice of the optimal corrective policy requires a complete understanding of the underlying non-cooperative behavior among governments. Our second main result is that neither revenue sharing or expenditure sharing can be sustained as a Nash equilibrium among governments, although all governments would benefit from one of these two corrective policies. Central intervention is therefore inevitable unless governments can pre-commit to the optimal corrective policy before setting their fiscal policies.     

关于手写汉字的切分算法的探讨

汉字识别是模式识别的一个重要分支。识别过程包括光电扫描,模数转换,预处理,模式表达,判别。其中预处理阶段的字切分是整个识别过程的一个重要组成部分,也是难点之一,使如污点的处理,粘连问题,字误切后的重新合并问题等,都给我们的准确切分带来许多麻烦。本文以确定的竖写字贴为处理对象,对手写汉字的字切分做了比较细致的工作,特别就以上提高的问题都是提出了比较实际的解决算法,整体上取得了良好的切分效果。     

中小企业股票市场化发行定价的半参数自组织模型与实证

随着深圳交易所中小企业板块的正式启动,我国中小企业新股发行的市场化定价方式必将启用。本文采用基于自组织数据挖掘GMDH算法的半参数模型的定价方法,将GMDH算法与半参数模型方法结合起来。不仅利用计算机的自动拟合优选最优复杂度模型,从而大大简化了非参数部分估计。创造了半参数模型崭新的实现方式,并达到了理想的定价效果,而且可以发挥半参数模型的特有优势。进行模型结构分析。经过实证和检验证明了这种模型用于我国股票发行定价的有效性和合理性。为完全市场化股票发行方式下确定股票的发行价格提供了新的方法。     

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。