Modeling the depletion of dissolved oxygen in a water body located near a city

Water bodies located nearby cities are much prone to pollution, especially in the developing countries, where effluents treatment facilities are generally lacking. The main reason for this phenomenon is the increasing population in the cities, and the large number of industries located near them. This leads to generation of huge amounts of domestic and industrial sewage that is discharged into the water bodies, increasing their organic pollutant load and resulting in the depletion of dissolved oxygen. In this paper, we propose a mathematical model for this situation, focusing especially on the resulting quality of the water, determined by the level of dissolved oxygen. The model also accounts for resources needed for the population survival and for the industrial operations. In addition, we describe also the decomposition of organic pollutants by bacteria in the aquatic medium. Feasibility conditions and stability criteria of the system's equilibria are determined analytically. The results show that human population and industries are relevant influential factors responsible for the increase in organic pollutants and the decrease in dissolved oxygen in the water body, in the sense that they may exert a destabilizing effect on the system. The numerical simulations confirm the analytical results. Copyright © 2016 John Wiley & Sons, Ltd.     

A solution approach for optimizing long- and short-term production scheduling at LKAB’s Kiruna mine

We present a mixed-integer program to schedule long- and short-term production at LKAB’s Kiruna mine, an underground sublevel caving mine located in northern Sweden. The model minimizes deviations from monthly preplanned production quantities while adhering to operational constraints. Because of the mathematical structure of the model and its moderately large size, instances spanning a time horizon of more than a year or two tend to be intractable. We develop an optimization-based decomposition heuristic that, on average, obtains better solutions faster than solving the model directly. We show that for realistic data sets, we can generate solutions with deviations that comprise about 3-6% of total demand in about a third of an hour.     

Alkyne hydroamination triggered cyclizations: A powerful tool for the construction of biologically important structural motifs

This review focuses mainly on recent endeavors in the field of cyclizations triggered by the catalytic hydroamination (formal or direct) of alkynes. The new strategies developed offer an efficient and convenient entry to several heterocycles of biological importance.     

改革开放以来我国产业结构的地区间比较及动态分析

产业结构提升是一国或地区经济素质的重要表现,是国民经济宏观管理的重要目标。本文对1978-2007我国产业结构的变化,以及地区间产业结构的相似性等问题进行了定量分析。主要内容包括:1978年以来全国产业结构的状况描述及变动检验,各地区产业结构变化及其与全国产业结构相比的类似性,产业结构特征的地区间分类。主要结论有:不论是从全国还是从各个地区来说我国三次产业结构变化总体上符合产业结构演变的规律;产业结构在地区间表现出较弱的不平衡性,没有出现整体性产业结构趋同化现象等。     

基于Bootstrap-DEA的工业能源效率分析

传统DEA方法存在小样本估计有偏、无法进行统计检验等缺点.而Bootstrap-DEA方法能够通过数值模拟技术产生大量的模拟样本,通过对新生成的样本进行估计来修正DEA效率估计偏差,进而计算出效率值的置信区间.作者利用Bootstrap-DEA方法首次对我国36个工业行业1995-2008年的能源利用效率进行分析.研究结果表明,我国工业行业的能源效率呈现出U字型变动趋势,行业间的能源效率差异不断减小.     

我国经济增长与产业结构演进关系的研究——基于面板数据模型的实证分析

本文运用面板数据模型,对我国各省1996-2005年人均GDP及三次产业产值比重的关系分别进行了模型拟合,结论认为:我国经济增长对产业结构变化的影响显著,而后者对前者的影响在统计上并不显著,我国经济增长模式是需求导向型的。其次,就各次产业与人均GDP的关系看,第一产业与人均GDP呈现负相关关系,而第二、三产业与人均GDP呈现正相关关系。     

求解全局最优问题的多重点样本水平值估计的相对熵算法

研究有界闭箱约束下的全局最优化问题,利用相对熵及广义方差函数方程的最大根与全局最小值之间的等价关系,设计求解全局最优值的积分型水平值估计算法.对采用重点样本采样技巧产生的函数值按一定规则进行聚类,从而在各聚类中产生的若干新重点样本,结合相对熵算法,构造出多重点样本进行全局搜索的新算法.该算法的优点在于每次迭代选用当前较好的函数值信息,以达到随机搜索到更好的函数值信息.同时多重点样本可有利挖掘出更好的全局信息.一系列的数值实验表明该算法是非常有效的.     

广义变系数模型的Bayesian B样条估计

提出了广义变系数模型函数系数的一种新的估计方法．我们用B样条函数逼近函数系数,不具体选择节点的个数,而是节点个数取均匀的无信息先验,样条函数系数取正态先验,用Bayesian模型平均的方法估计各个函数系数．这种估计方法一个主要特点是允许各个函数系数所需节点个数的后验分布不同,因此允许不同函数系数使用不同的光滑参数．另外,本文还给出了Bayesian B样条估计的计算方法,并通过模拟例子,说明广义变系数模型的函数系数可以由Bayesian B样条估计方法得到很好的估计．     

Buffer sizing in multi-product multi-reactor batch processes: Impact of allocation and campaign sizing policies

This paper studies the impact of management policies, such as product allocation and campaign sizing, on the required size of the finished goods inventories in a multi-product multi-reactor batch process. Demand, setup and batch processing times for these products are assumed to be stochastic, and the inventory buffer for every product type needs to be such that target customer service levels are met. To perform this analysis, we develop a queueing model that allows us to explicitly estimate service levels as a function of the buffer size, and the allocation/campaign sizing policies. This model can be used to evaluate the service level given an existing buffer configuration, as well as to determine the buffer sizes required across products to meet a pre-specified service level. It also allows us to formulate a number of insights into how product allocation decisions and campaign planning policies affect buffer sizing decisions in symmetric production systems.     

A dynamic production planning and scheduling algorithm for two products processed on one line

This paper presents a dynamic production planning and scheduling algorithm for two products processed on one line over a fixed time horizon. Production rates are assumed fixed, and restrictions are placed or inventory levels and production run lengths. The resulting problem is a nonlinear binary program, which is solved using an implicit enumeration strategy. The algorithm focuses on the run changeover period while developing tighter bounds on the length of the upcoming run to improve computational efficiency. About 99% pf 297 randomly generated problems with varying demand patterns are solved in less than 15 seconds of CPU time on a CDC Cyber 172 Computer. A mixed integer programming formulation of the generalized multi-product case under no-backlogging of demand is also given.