多储备点多品种应急物资配送的多目标优化模型

应急救援的社会化、应急物资需求的多样性、应急物资需求和补给的时变性,对应急物流的配送调度提出了挑战.应急物流的紧急性要求最大程度保障受灾点的物资供应;在经济上则要求应急物流的成本最小化.通过将时间离散化为阶段序列,在应急物资需求和补给是可预测的情况下,建立一个多储备点、多物资品种、单受灾点的应急物资配送的多目标优化模型,来最小化应急物资短缺次数和运输成本.仿真实例表明,该模型可以通过优化引擎快速求解,能够发现导致短缺的应急物资品种和加强供应补给的时间区间.     

成交量信息有助于预测中国股票市场的波动吗?

就成交量信息是否有助于预测股票市场的波动率这一问题,目前学术界有两种截然相反的观点存在。本文以中国股票市场代表性指数的代表性波动周期为例,对上述问题进行了实证研究。通过采用较以往研究更为严谨和稳健的样本外滚动时间窗预测法和高级预测能力检验法(Superiorpredictive ability,SPA),本文得到的分析结论包括:(1)成交量信息对中国股票市场的波动过程有显著影响;(2)将成交量纳入GARCH族模型会导致条件方差方程中的波动持续性出现明显下降;(3)引入成交量作为附加解释变量的GARCH族模型并未表现出比一般GARCH族模型更优的波动率预测能力。最后对实证结果给出了理论解释。     

Application of seasonal SVR with chaotic gravitational search algorithm in electricity forecasting

Hybridization chaotic mapping functions with optimization algorithms into a support vector regression model has been shown its efficient potential to avoid converging prematurely. It is deserved to explore more possibility by hybridizing with other optimization algorithms. Electricity demand sometimes demonstrates a seasonal tendency due to complicate economic activities or climate cyclic nature. This investigation presents a SVR-based electricity forecasting model which applied a novel hybrid algorithm, namely chaotic gravitational search algorithm (CGSA), to improve the forecasting performance. The proposed CGSA employs the chaotic local search by logistic chaotic mapping function in the iteration of the original GSA to search and refine the current best solution. In addition, seasonal mechanism is also applied to deal with seasonal electricity tendency. A numerical example from an existed reference is used to illustrate the forecasting performance of the proposed SSVRCGSA model. The forecasting results indicate that the proposed model yields more accurate forecasting results than ARIMA and TF-ε-SVR-SA models.     

Profit maximization in simultaneous lot-sizing and scheduling problem

This paper extends the simultaneous lot-sizing and scheduling problem, to include demand choice flexibility. The basic assumption in most research about lot-sizing and scheduling problems is that all the demands should be satisfied. However, in a business with a goal of maximizing profit, meeting all demands may not be an optimum decision. In the profit maximization simultaneous lot-sizing and scheduling problem with demand choice flexibility, the accepted demand in each period, lot-sizing and scheduling are three problems which are considered simultaneously. In other words the decisions pertaining to mid-term planning and short-term planning are considered as one problem and not hierarchically. According to this assumption, the objective function of traditional models changes from minimizing costs to maximizing profits.     

A pro-active real-time control approach for dynamic vehicle routing problems dealing with the delivery of urgent goods

This paper proposes a new pro-active real-time control approach for dynamic vehicle routing problems in which the urgent delivery of goods is of utmost importance. Without assuming any distribution, stochastic knowledge about future requests is generated using past request information. The generated knowledge is integrated into the transportation process, which is controlled by a Tabu Search algorithm, in order to actively guide vehicles to request-likely areas before requests arrive there. By analyzing the results attained for various test settings, we identify structural diversity as a crucial criterion for classifying the quality of stochastic knowledge attainable from past request information. This criterion provides a promising starting point for assessing the quality of past request information in order to efficiently use the derived stochastic knowledge in real-time control approaches. We prove the efficiency of our approach by a direct comparison with a deterministic approach on test scenarios with varying structural diversity. Thanks to the proposed classification of structural diversity, differences in results obtained among the tested scenarios become explainable.     

低碳经济背景下中国铅精炼企业产销存量预测的ARMA模型构建及其应用研究

分析了ARMA模型构建中的数学方法,构建了低碳经济背景下中国铅精炼企业产销存量预测的ARMA模型,检验结果显示,ARMA(4,0)模型是对低碳经济背景下中国铅精炼企业产销存量进行短期预测的较优模型,同时最后采用该模型对中国铅精炼企业未来5年的产销存量进行了预测,并就预测结果提出了促进我国精炼铅市场低碳可持续发展的三种政策建议。     

基于季节ARIMA模型的电力系统负荷短期预测

电力负荷是影响电网寿命和可靠度的一个重要因素,其月负荷变化具有明显的周期性.介绍了应用季节ARIMA模型进行电力负荷建模预测的理论和方法,将季节ARIMA模型应用于电力系统负荷短期预测,测试结果证明了方法的有效性.     

主成分回归分光光度法测定化学需氧量的研究

采用主成分回归校正技术辅助分光光度法很好地解决了光度法化学需氧量测定中共存金属离子的干扰问题。在实验的基础上 ,选取了 Cu2 、Fe3 、Co2 、Mn2 、Ni2 作为主要的干扰离子 ,通过对多个样品的分析 ,确定了最优分析波长组 ,并对 19个实际样品进行了测量 ,结果表明 ,本法测定结果与国标推荐方法无明显差异 ,具有操作简便、测定快速的优点。     

Forecasting model with asymmetric market response and its application to pricing of consumer package goods

This paper presents a dynamic forecasting model that accommodates asymmetric market responses to marketing mix variable—price promotion—by threshold models. As a threshold variable to generate a mechanism for different market responses, we use the counterpart to the concept of a price threshold applied to a representative consumer in a store. A Bayesian approach is taken for statistical modelling because of advantages that it offers over estimation and forecasting. The proposed model incorporates the lagged effects of a price variable. Thereby, myriad pricing strategies can be implemented in the time horizon. Their effectiveness can be evaluated using the predictive density. We intend to improve the forecasting performance over conventional linear time series models. Furthermore, we discuss efficient dynamic pricing in a store using strategic simulations under some scenarios suggested by an estimated structure of the models. Empirical studies illustrate the superior forecasting performance of our model against conventional linear models in terms of the root mean square error of the forecasts. Useful information for dynamic pricing is derived from its structural parameter estimates. This paper develops a dynamic forecasting model that accommodates asymmetric market responses to marketing mix variable—price promotion—by the threshold models. Copyright © 2005 John Wiley & Sons, Ltd.