冲击模型:进展与应用

综述了近30年来冲击模型研究的主要进展.介绍了一个新模型(δ-冲击模型)及其最新工作.基于簇生标值点过程的结构,给出了冲击模型的一个一般性框架,最后作为特例提出并分析了一个新的保险风险模型.     

模糊反向物流网络设计模型的一种改进遗传算法

反向物流是物流研究中的一个重要分支,其相关问题是目前研究的热点问题。该研究在模糊环境中根据不同的决策标准,建立了关于反向物流问题中的回收问题的三种不同类型的模型:期望值模型,机会约束模型和相关机会模型,并设计了一个模糊模拟和遗传算法相结合的混合智能算法来解决提出的模型,最后给出了一个数值例子,结果证明了将此混合智能算法用于求解模糊反向物流网络设计模型问题的有效性。     

模糊环境下动态供应商选择的混合整数非线性规划模型

基于供应商选择问题的动态性和模糊性,考虑在每个周期内生产商的需求能力及供应商的供应能力为模糊变量,本文将一个多阶段多商品多渠道的供应商选择问题视为一个0-1混合整数模糊动态非线性规划问题,目标函数为总成本最小化。然后建立了0-1混合整数模糊动态非线性规划模型。为了求解该模型,通过可信性理论把模型中模糊机会约束清晰化,将该模型转化为一个确定型的0-1混合整数动态非线性规划模型。最后给出了一个数值算例验证了模型的可行性。     

多指标席位分配模型及其应用

将经典席位分配模型推广,建立了多指标席位分配模型,它是一个有界整数变量非线性规划模型。将模型转化为非线性连续规划模型,因而可用各种具有良好收敛性和收敛速度的求解非线性连续规划的算法求解。给出多指标席位分配模型的一个简单有效的算法。最后实例说明多指标席位分配模型应用更加合理、更加广泛。     

考虑供应链风险和绩效的供应商选择的模糊动态非线性多目标规划模型

基于供应链风险和供应链绩效的模糊性和供应商选择问题的动态性,本文考虑供应链风险和供应链绩效作为模糊变量,讨论如何给生产商一个满意的动态多目标供应商选择方案,确定供应链风险和总成本最小,以及供应链绩效最大。然后对该问题提出了一个动态多目标多产品供应商选择模型,该模型是首次同时考虑供应商选择,订单分配,供应链风险和供应链绩效的一个模糊动态非线性多目标规划模型。为了去模糊化和求解该模型,给出了一个风险和绩效的模糊评估法。最后给出一个数值算例验证了该模型的可行性,为决策者选择供应商提供了理论依据。     

带ARMA(1,1)条件异方差相关的随机波动模型的MCMC算法

我们首先提出了一个带ARMA(1,1)条件异方差相关的随机波动模型,它是基本的随机波动模型的一个自然的推广.进一步,对于这一新模型,我们给出了一个马尔可夫链蒙特卡罗(M CM C)算法.最后,利用该模型的模拟数据,展示了M CM C算法在这种模型中的应用.     

基于数据和整体的航空网络静态定价模型

建立了一个静态定价与座位分配联合模型.利用模型的性质,将问题简化为一个可分的凹规划模型.特别地,在一个三航段网络上,从模型的网络流形式推出最优目标函数具有良好的性质,并对模型的最优价格决策进行了灵敏度分析.最后给出了一个双枢纽网络上对细分产品定价的算例.     

基于蒙特卡洛-马尔科夫链(MCMC)的ARMA模型选择

AIC与SIC等准则函数方法是ARMA模型选择过程中经常使用的方法。但是,当模型的阶数很高时,无法计算并比较每一个备选模型的准则函数值。本文提出了一个基于蒙特卡洛-马尔科夫链方法的随机模型生成方法,以产生准则函数值最小的备选模型。实际应用表明本文的方法在处理拥有大量备选模型的ARMA模型选择问题时有很好的效果。     

应用联合分析和混合回归模型进行市场细分

联合分析是一种有效地反映消费者需求差异的方法,所以被广泛地应用到市场细分的研究中。但是,传统的方法存在着一定的不足。本研究提出了一个残差分布假设不同的混合回归模型,模型估计的效率比较高,而且模型系数也必较可靠。所以不失为一个比较理想的市场细分分析工具。本文应用该模型方法对一个笔记本电脑联合分析案例进行了实证分析。     

基于可信性理论的生产计划期望值模型

基于可信性理论,提出一类新的模糊生产计划期望值模型.然后,讨论这个模糊生产计划模型的基本性质.最后,利用这个模糊模型的基本性质我们可以把模糊生产计划期望值模型转化为一个线性规划模型并且设计相应的算法求解模糊生产计划问题的一个数值例子.     

Optimizing the positioning and technological choices of RFID elements for aircraft part identification

This paper concerns the integration of RFID (Radio Frequency IDentification) technologies in helicopters. A global RFID system, including RFID tags (passive, battery assisted and active), reading modules and data concentrator, will be embedded in helicopters. Such an integration requires a positioning model, which must consider technological choices of the on-board components. The proposed approach combines an optimization model and a physical model to determine an optimal covering of each tag by at least one reading module. This covering is based on radio wave propagation. The optimization model is derived from a location model with specific constraints. Experimental results validate the approach in an industrial context.     

N.E.W.S.: A model for the evaluation of non-life insurance companies

This paper describes a model which can be used by the Dutch insurance supervisor to determine the priority a non-life insurer should have for further examination. This model combines a traditional statistical technique (an ordered logit model) with artificial intelligence techniques (a neural network and an expert system). The output of the model consists of the priority for further examination (high, medium, or low), and a report which summarizes the main findings of the model. The model was able to adequately classify 93% of the companies in a 1993 data set.     

Maximum Likelihood Estimation of the Markov-Switching GARCH Model Based on a General Collapsing Procedure

The Markov-switching GARCH model allows for a GARCH structure with time-varying parameters. This flexibility is unfortunately undermined by a path dependence problem which complicates the parameter estimation process. This problem led to the development of computationally intensive estimation methods and to simpler techniques based on an approximation of the model, known as collapsing procedures. This article develops an original algorithm to conduct maximum likelihood inference in the Markov-switching GARCH model, generalizing and improving previously proposed collapsing approaches. A new relationship between particle filtering and collapsing procedures is established which reveals that this algorithm corresponds to a deterministic particle filter. Simulation and empirical studies show that the proposed method allows for a fast and accurate estimation of the model.     

HARVESTING AN AGE‐STRUCTURED POPULATION AS BIOMASS: DOES IT WORK?

Abstract The economics of fisheries is based heavily on describing fish populations by the surplus production model. Both economists and ecologists have different opinions on whether this approach provides an adequate biological basis for economic analysis. This study takes an age‐structured population model and shows how, under equilibrium conditions, it determines the surplus production model. The surplus production model is then used to solve an optimal feedback policy for a generic optimal harvesting problem. Next, it is assumed that the fishery manager applies this feedback policy even though the fish population actually evolves according to the age‐structured model. This framework is applied to the widow rockfish, Atlantic menhaden, and Pacific halibut fisheries. Population age‐structure contains information on future harvest possibilities. The surplus production model neglects this information and may lead to major deviations between the expected and actual outcomes especially under multiple steady states and nonlinearities.     

The direct updating of damping and gyroscopic matrices

In this paper we develop an efficient numerical method for the finite element model updating of damped gyroscopic systems. This model updating of damped gyroscopic systems is proposed to incorporate the measured modal data into the finite element model to produce an adjusted finite element model on the damping and gyroscopic matrices that closely match the experimental modal data.     

投资环境地区横向比较

本文以各地区经济数据为基础,通过建立统计分析的数学模型,给出了度量、评测投资环境的客观标准,并应该标准对几个典型城投资环境进行评价和分类,从一个新的角度,就客观、定量的研究投资环境进行了探索.     

Dynamic systems identification with Gaussian processes

This paper describes the identification of nonlinear dynamic systems with a Gaussian process (GP) prior model. This model is an example of the use of a probabilistic non-parametric modelling approach. GPs are flexible models capable of modelling complex nonlinear systems. Also, an attractive feature of this model is that the variance associated with the model response is readily obtained, and it can be used to highlight areas of the input space where prediction quality is poor, owing to the lack of data or complexity (high variance). We illustrate the GP modelling technique on a simulated example of a nonlinear system.     

AN IMPROVED m-DIMENSIONAL CER MODEL FOR ASSESSMENT OF THE SYNTHETICAL POLLUTION STATUS OF ENVIRONMENT

In this paper, a new mathematical model is constructed on the basis of an earlier paper [1]. This model can be employed to assess various types of synthetical pollution status of the environment, when the contents of some pollutants in the environment are beyond the limits of the standard of GB or WHO/FAO. This model is an improved m-dimensional CER model with classified structure. It will have broader application in practice.     

A framelet algorithm for de-blurring images corrupted by multiplicative noise

This paper considers a variational model for restoring images from blurry and speckled observations. This model utilizes the favorable properties of framelet regularization (e.g., the sparsity and multiresolution properties of the framelet) that are well suited for speckle noise reduction. For solving the model, we first propose an approximation model that is motivated by the well-known variable-splitting and penalty techniques in optimization. We then develop an alternating minimization algorithm to solve the approximation model. We also show that the sequence generated by the algorithm converges to the solution of the proposed model. The numerical results on simulated data and real utrasound images demonstrate that our approach outperforms several state-of-the-art algorithms.     

Fuzzy inventory problems for perishable commodities

This paper considers an inventory control model for a single perishable product with a fuzzy shortage cost and a fuzzy outdating cost. This model is a single-period horizon model. Due to fuzziness of shortage and outdating costs, an expected profit function is represented with a fuzzy set. The purpose of this paper is to find the solution maximizing the expected profit function. After defining a nondominated ordering quantity based on fuzzy max order, we seek some of them and investigate an effect of the fuzziness on the obtained solutions.