Stochastic call center staffing with uncertain arrival,service and abandonment rates: A Bayesian perspective

In this article, we introduce staffing strategies for the Erlang‐A queuing system in call center operations with uncertain arrival, service, and abandonment rates. In doing so, we model the system rates using gamma distributions that create randomness in operating characteristics used in the optimization formulation. We divide the day into discrete time intervals where a simulation based stochastic programming method is used to determine staffing levels. More specifically, we develop a model to select the optimal number of agents required for a given time interval by minimizing an expected cost function, which consists of agent and abandonment (opportunity) costs, while considering the service quality requirements such as the delay probability. The objective function as well as the constraints in our formulation are random variables. The novelty of our approach is to introduce a solution method for the staffing of an operation where all three system rates (arrival, service, and abandonment) are random variables. We illustrate the use of the proposed model using both real and simulated call center data. In addition, we provide solution comparisons across different formulations, consider a dynamic extension, and discuss sensitivity implications of changing constraint upper bounds as well as prior hyper‐parameters. © 2016 Wiley Periodicals, Inc. Naval Research Logistics 63: 460–478, 2016     

Thirty Years of Conflict and Economic Growth in Turkey: A Synthetic Control Approach

Abstract

This study seeks to estimate the causal effects of PKK separatist terrorism on economic development in Turkey using the synthetic control method. By creating a synthetic control group that reproduces the Turkish Gross Domestic Product (GDP) before PKK terrorism emerged in the late 1980s, we compare the GDP of the synthetic Turkey and the actual for the period 1955–2008. Our study finds that the Turkish per capita GDP would have been higher by about $2600 had it not been exposed to terrorism. This translates into an average of 21.4% higher per capita GDP over a period of 21 years.     

基于模糊论的复杂系统故障诊断专家系统设计

复杂系统中广泛存在着模糊问题,故障与征兆之间的关系更具有模糊性.首先简要介绍了模糊评判的基本原理及其数学模型,提出了将模糊综合评判应用于复杂系统故障诊断专家系统的新思路,重点分析了复杂系统知识信息的获取与表示方法,给出了知识库的建立及推理过程.证明了某型导弹测试设备故障诊断专家系统组建方法的可行性.     

Progressive Type‐II censoring and coherent systems

A new connection between the distribution of component failure times of a coherent system and (adaptive) progressively Type‐II censored order statistics is established. Utilizing this property, we develop inferential procedures when the data is given by all component failures until system failure in two scenarios: In the case of complete information, we assume that the failed component is also observed whereas in the case of incomplete information, we have only information about the failure times but not about the components which have failed. In the first setting, we show that inferential methods for adaptive progressively Type‐II censored data can directly be applied to the problem. For incomplete information, we face the problem that the corresponding censoring plan is not observed and that the available inferential procedures depend on the knowledge of the used censoring plan. To get estimates for distributional parameters, we propose maximum likelihood estimators which can be obtained by solving the likelihood equations directly or via an Expectation‐Maximization‐algorithm type procedure. For an exponential distribution, we discuss also a linear estimator to estimate the mean. Moreover, we establish exact distributions for some estimators in the exponential case which can be used, for example, to construct exact confidence intervals. The results are illustrated by a five component bridge system. © 2015 Wiley Periodicals, Inc. Naval Research Logistics 62: 512–530, 2015     

基于ANFIS的目标毁伤等级预测模型

分析了神经网络和模糊推理系统的优缺点,研究了自适应神经模糊推理系统（ANFIS）结构模型及后向传播和递归最小二乘算法相结合的混合算法．在分析了目标毁伤等级主要影响因素的基础上,构建了目标毁伤等级预测ANFIS模型,利用毁伤试验样本数据训练该模型,得到了与实际一致的目标毁伤等级,并将预测结果与基于BP神经网络的预测结果进行了仿真对比分析．仿真结果表明,该目标毁伤等级预测模型能够准确地预测出目标的毁伤等级,并且其预测精度较BP神经网络方法高,为目标毁伤等级预测提供了一种有效的方法．     

发动机传感器数据证实的贝叶斯信度网络方法

针对发动机及其部件试验传感器数据证实的多源证据融合问题,描述了建立贝叶斯信度网络的方法,给出了传感器状态和检验关系式不确定性信息表达方法,发展了自动建立贝叶斯信度网络、计算可信度概率及更新网络的算法;给出了贝叶斯信度网络方法在模型发动机上的应用示例。     

谈英语教学的语用观

语用知识对学生理解和使用语言有着非常重要的作用。只有具备了一定的语用知识,学生才能准确地使用语言,才能真正学会一门语言。这就要求英语教师在讲解语言知识的同时一定要注重语用知识的传授。     

推理树概率逻辑公式集有效赋值列数计算

本文通过对概率逻辑推理树知识结构模型的研究,得出在树推理中对矩阵列消减起主要作用的相邻关系及其计算方法,给出了树推理模型的有效赋值列数的一般计算方法。     

一个多Agent系统合作模型

从多Agent系统的组成结构出发,综述合作问题的理论机制,提出了采用多Agent系统模型来求解逻辑推理问题的方法,根据各Agent自身意图,相互合作以达成群体目标。     

基于模糊推理的目标攻潜武器判断

介绍了模糊推理理论基本思想,分析了判断目标攻潜武器的战术依据.针对潜艇水下收集目标信息的特点,应用模糊推理理论建立了目标攻潜武器类型的判断规则,并给出推导过程和实现方式,在把模糊推理理论应用于潜艇威胁判断模型的研究上做了初步尝试.