Base station location and channel allocation in a cellular network with emergency coverage requirements

The location of base stations (BS) and the allocation of channels are of paramount importance for the performance of cellular radio networks. Also cellular service providers are now being driven by the goal to enhance performance, particularly as it relates to the receipt and transmission of emergency crash notification messages generated by automobile telematics systems. In this paper, a Mixed Integer Programming (MIP) problem is proposed, which integrates into the same model the base station location problem, the frequency channel assignment problem and the emergency notification problem. The purpose of unifying these three problems in the same model is to treat the tradeoffs among them, providing a higher quality solution to the cellular system design. Some properties of the formulation are proposed that give us more insight into the problem structure. An instance generator is developed that randomly creates test problems. A few greedy heuristics are proposed to obtain quick solutions that turn out to be very good in some cases. To further improve the optimality gap, we develop a Lagrangean heuristic technique that builds on the solution obtained by the greedy heuristics. Finally, the performance of these methods is analyzed by extensive numerical tests and a sample case study is presented.     

An approach to modelling industrial unit processes: application to a spiral concentrator for minerals

A suite of computer models which simulate process operations in common use in the minerals processing industry is being developed. Application of the models is described with reference to a particular process device, the spiral concentrator. The paper sets out to explain the basic strategy behind the unit process modelling approach and discusses in detail the overall model structure adopted. The model aims to provide a set of equations, with sufficient physical significance to give a reasonable fit to any specific data set, and which can be systematically adjusted (through auxiliary models, user judgement and experience) to provide meaningful performance predictions over a broad range of operating conditions. The approach is thought to be applicable to a wide variety of processes. The model has been tested using a variety of ores, separated on plant-scale equipment and practical examples are given. The scope and limitations of the method are reported, drawing on the results of parallel experimental work. The extent to which this kind of approach can be used as a predictive tool in process design applications and in the day-to-day running of mineral processing plant is discussed.     

一种基于集成学习的试题多知识点标注方法

个性化试题推荐、试题难度预测、学习者建模等教育数据挖掘任务需要使用到学生作答数据资源及试题知识点标注,现阶段的试题数据都是由人工标注知识点。因此,利用机器学习方法自动标注试题知识点是一项迫切的需求。针对海量试题资源情况下的试题知识点自动标注问题,本文提出了一种基于集成学习的试题多知识点标注方法。首先,形式化定义了试题知识点标注问题,并借助教材目录和领域知识构建知识点的知识图谱作为类别标签。其次,采用基于集成学习的方法训练多个支持向量机作为基分类器,筛选出表现优异的基分类器进行集成,构建出试题多知识点标注模型。最后,以某在线教育平台数据库中的高中数学试题为实验数据集,应用所提方法预测试题考察的知识点,取得了较好的效果。     

Finite population cellular radio systems with directed retry

This paper proposes an analytically tractable model to predict the performance of cellular communication nonhomogeneous traffic originated from finite population in cellular radio system. In many locations in cellular radio network, there is overlapping coverage, usually by nearby base stations. This coverage can be shared by mobile users of more than one base station (BS) to improve the teletraffic performance characteristics. We study directed retry assignment scheme which allows a call to access the neighbouring BS in case it cannot be served by the BS in which it is located. Various system performace measures viz. blocking probabilities for different traffics, overall blocking probability and offered carried load are determined. Analytical results are compared with simulations to verify the validity of the proposed algorithm. It is shown that by increasing overlapping coverage area, a substantial improvement can be achieved.     

Optimal Network Design for Wireless Local Area Network

Network design for wireless local area networks is an important issue in the deployment of these networks. Research activities are presently being undertaken in two major areas: determining the location of base stations (BSs) and assigning the frequency channels for these stations. Our BS location problem selects a set of BSs to provide the best demand area coverage and maximize the signal level and physical area attendance priority. Adequate channel assignment reduces signal interference and improves network throughput. This paper reports a real world experiment where we applied the concepts of two classical outdoor problems namely the optimal BS location problem and the fixed channel assignment problem to build a WLAN into an indoor environment. We propose a mathematical model that we solve by a commercial software and report the computational results.     

基于无线通信基站的室内三维定位问题研究

对基于无线通信基站的室内三维定位问题进行了研究,建立了测量误差模型和终端定位模型.建立了TOA测量误差模型和基于测量误差估计的终端定位模型,提出了基于空间几何约束和测量噪声抑制的定位算法;分别在相对时间误差、最大时延、最小时延和随机法四种基站筛选方案下,分析了不同基站数目对定位精度的影响;利用轨迹上相近点的信道状态信息的相关性,采用Kalman滤波算法计算了终端运动轨迹;基于假设性检验,通过递减迭代搜索算法,得到了可定位终端数;建立了基站不同覆盖范围下,终端连接度数与定位精度之间关系的分析模型.     

Automated antenna positioning algorithms for wireless fixed-access networks

This article addresses a real-life problem - obtaining communication links between multiple base station sites, by positioning a minimal set of fixed-access relay antenna sites on a given terrain. Reducing the number of relay antenna sites is considered critical due to substantial installation and maintenance costs. Despite the significant cost saved by eliminating even a single antenna site, an inefficient manual approach is employed due to the computational complexity of the problem. From the theoretical point of view we show that this problem is not only NP hard, but also does not have a constant approximation. In this paper we suggest several alternative automated heuristics, relying on terrain preprocessing to find educated potential points for positioning relay stations. A large-scale computer-based experiment consisting of approximately 7,000 different scenarios was conducted. The quality of alternative solutions was compared by isolating and displaying factors that were found to affect the standard deviation of the solutions supplied by the tested heuristics. The results of the simulation based experiments show that the saving potential increases when more base stations are needed to be interconnected. The designs of a human expert were compared to the automatically generated solutions for a small subset of the experiment scenarios. Our studies indicate that for small networks (e.g., connecting up to ten base stations), the results obtained by human experts are adequate although they rarely exceed the quality of automated alternatives. However, the process of obtaining these results in comparison to automated heuristics is longer. In addition, when more base station sites need to be interconnected, the human approach is easily outperformed by our heuristics, both in terms of better results (fewer antennas) and in significant shorter calculation times.     

基于无线通信基站三维定位问题的求解模型

基于无线通信基站的三维定位相比于传统GPS定位有着诸多优势,技术有着广阔的应用前景和巨大的商业价值.针对基于无线通信基站的三维定位问题,首先分析建立TOA定位的初步模型.其次,基于对模型时钟误差、非视距传播误差、测量误差的分析,优化方程组的建立策略,基站排序,方程组系数修正的方式,使误差项的影响降到最小.最终由最小二乘法计算出定位结果.实验表明,定位模型的定位精度在1米左右,并且定位精度随基站数目的增多而增高.     

Wireless network capacity management: A real options approach

This paper applies financial option valuation methods to new wireless network capacity investment decision timing. In particular, we consider the case of network capacity for cellular telephone service. Given a cluster of base stations (with a certain traffic capacity per base station), we determine when it is optimal to increase capacity for each of the base stations contained in the cluster. We express this in terms of the fraction of total cluster capacity in use, i.e. we calculate the optimal time to upgrade in terms of the ratio of observed usage to existing capacity. We study the optimal decision problem of adding new capacity in the presence of stochastic wireless demand for services. A four factor algorithm is developed, based on a real options formulation. Numerical examples are provided to illustrate various aspects of the model.     

Application of a location model to fire stations in Rotterdam

This report is an outgrowth of a research project carried out by the Operations Research Group of Twente University of Technology in cooperation with the Department Fire-Brigade Affairs (Home Office) and the Rotterdam Fire Department. The objectives of the project were to determine the minimal number of fire stations, their locations and the number of first attendance pumpers, so that each point in town can be reached within a prescribed attendance time with sufficient equipment.A road network approach was used for determining the set of possible location areas for fire stations followed by a set-covering approach for calculating the minimal number of stations. The hard points to tackle were the construction of robust networks, the determination of the possible location areas and the calculation of all the alternative locations of a minimal number of fire stations.A simulation was carried out to test whether the solutions given by the network approach were realistic.     

Optimizing the Design of a CDMA Cellular System Configuration with Multiple Criteria

This paper deals with the mathematical modeling and optimization of a code division multiple access (CDMA) cellular system configuration that seeks the optimal location, power, and antenna height of each base station in a service area, in order to optimize call quality, service coverage and total cost of system configuration. The factors affecting optimum selection are the non-uniform spatial demand in the service area, the propagation environment, the interference among users and among base stations, and other factors intrinsic to CDMA technology. The simulated annealing method supplemented by a demand allocation algorithm is implemented in a software package to solve this complex multiobjective nonlinear optimization problem. This research shows that simulated annealing is a viable method for obtaining good quality solutions to the wireless system configuration problem. A realistic case study dealing with the design of a cellular system configuration for the city of Cambridge, MA, and its surroundings, is developed to illustrate the modeling concept and the steps of the algorithm. Sensitivity analysis is performed to further analyze the configuration decision.     

Regularized optimization methods for convex MINLP problems

We propose regularized cutting-plane methods for solving mixed-integer nonlinear programming problems with nonsmooth convex objective and constraint functions. The given methods iteratively search for trial points in certain localizer sets, constructed by employing linearizations of the involved functions. New trial points can be chosen in several ways; for instance, by minimizing a regularized cutting-plane model if functions are costly. When dealing with hard-to-evaluate functions, the goal is to solve the optimization problem by performing as few function evaluations as possible. Numerical experiments comparing the proposed algorithms with classical methods in this area show the effectiveness of our approach.     

Adaptive surrogate-based design optimization with expected improvement used as infill criterion

A prominent advantage of using surrogate models in structural design optimization is that computational effort can be greatly reduced without significantly compromising model accuracy. The essential goal is to perform the design optimization with fewer evaluations of the typically finite element analysis and ensuring accuracy of the optimization results. An adaptive surrogate based design optimization framework is proposed, in which Latin hypercube sampling and Kriging are used to build surrogate models. Accuracy of the models is improved adaptively using an infill criterion called expected improvement (EI). It is the anticipated improvement that an interpolation point will lead to the current surrogate models. The point that will lead to the maximum EI is searched and used as infill points at each iteration. For constrained optimization problems, the surrogate of constraint is also utilized to form a constrained EI as the corresponding infill criterion. Computational trials on mathematical test functions and on a three-dimensional aircraft wing model are carried out to test the feasibility of this method. Compared with the traditional surrogate base design optimization and direct optimization methods, this method can find the optimum design with fewer evaluations of the original system model and maintain good accuracy.     

Carbon tax based on the emission factor: a bilevel programming approach

We present a bilevel programming approach to design an effective carbon tax scheme based on the production emission factor, used as an intensity measure, for a competitive market with multiple players. At the upper level, the government sets a target emission factor for the industry and taxes firms if they exceed that target. At the lower level, the industry sets output levels that maximize social welfare. The bilevel model is transformed to a linear MIP by replacing the lower level optimization problem by its KKT conditions, and linearizing the complementarity slackness conditions. We test the model in the context of the cement industry. The results show that the proposed model finds the optimal tax rate that induces firms to switch to less carbon-intensive fuels and reduces the overall emissions.     

Optimizing base station location and configuration in UMTS networks

Radio planning and coverage optimization are critical issues when deploying and expanding third generation cellular systems. We investigate mixed integer programming models for locating and configuring base stations in UMTS networks so as to maximize coverage and minimize installation costs. The overall model considers both uplink and downlink directions, that we studied separately in Amaldi et al. (2002, 2003b). The two-stage Tabu Search algorithm we propose exploits solutions of a simplified model for the uplink direction to drastically reduce the computational time required to find good approximate solutions of the overall uplink and downlink model.Computational results obtained for realistic instances %with voice as well as data traffic are reported and discussed. Research carried out within the national project “Optimization, simulation and complexity in the design and management of telecommunication networks”funded by the Italian Ministry of Education, University and Scientific Research (MIUR).     

Combining boosting and evolutionary algorithms for learning of fuzzy classification rules

This paper presents a novel boosting algorithm for genetic learning of fuzzy classification rules. The method is based on the iterative rule learning approach to fuzzy rule base system design. The fuzzy rule base is generated in an incremental fashion, in that the evolutionary algorithm optimizes one fuzzy classifier rule at a time. The boosting mechanism reduces the weight of those training instances that are classified correctly by the new rule. Therefore, the next rule generation cycle focuses on fuzzy rules that account for the currently uncovered or misclassified instances. The weight of a fuzzy rule reflects the relative strength the boosting algorithm assigns to the rule class when it aggregates the casted votes. The approach is compared with other classification algorithms for a number problem sets from the UCI repository.     

A novel piecewise linear classifier based on polyhedral conic and max–min separabilities

In this paper, an algorithm for finding piecewise linear boundaries between pattern classes is developed. This algorithm consists of two main stages. In the first stage, a polyhedral conic set is used to identify data points which lie inside their classes, and in the second stage we exclude those points to compute a piecewise linear boundary using the remaining data points. Piecewise linear boundaries are computed incrementally starting with one hyperplane. Such an approach allows one to significantly reduce the computational effort in many large data sets. Results of numerical experiments are reported. These results demonstrate that the new algorithm consistently produces a good test set accuracy on most data sets comparing with a number of other mainstream classifiers.     

一种基于二部图的试题知识点标注方法

针对在线教育中试题知识点自动标注问题,本文提出了一种基于二部图的试题知识点标注方法。首先,为了合理划分知识点粒度,本文构建了知识点知识图谱来融合知识点;其次,基于教材等语料抽取知识点与特征词二部图和试题与特征词二部图,并利用TF-IDF公式计算知识点与特征词、试题与特征词之间的边权,以构建试题-知识点二部图模型;再次,提出词频加权的相似性度量方法计算试题和知识点之间的相似度,将相似度最高的知识点作为试题知识点标签。最后,以某在线教育平台提供的高中历史试题为实验数据集进行数值实验,实验结果表明该方法的效果显著优于朴素贝叶斯、K最近邻、随机森林以及支持向量机。     

Using mathematical programming heuristics in a multicriteria network flow context

In this paper, we propose a local search procedure to test the robustness of a specific ‘satisfying point’ neighbourhood. It consists of the following steps: (1) build an indifference area around the satisfying point in the criteria space by using thresholds (this takes into account the possible uncertainty, vagueness and/or inaccuracy of data); (2) find some points in the satisfying point neighbourhood and the corresponding solutions in the decision variables space; (3) test the quality of these solutions from the point of view of user preference. The indifference area is defined by adding constraints to the network model. This approach, which allows us to verify the adequacy of the model, has been applied to a set of multicriteria network flow problems. A heuristic method, based on Lagrangian duality and subgradient techniques, exploits the combinatorial structure of network flow problems in order to find certain feasible points.     

基地化保障模式下飞机四站装备需求确定研究

基地化保障模式对飞机保障资源需求的影响是制约其发展的重要问题.基于离散事件仿真(DES)方法建立了航空兵场站四站保障过程的数学模型,考虑了四站装备自身故障的影响,并在所建模型的基础上提出运用离散系统仿真软件ARENA对四站保障过程进行仿真.仿真结果表明,与现行的航空兵场站单机种保障策略相比,基地化保障模式能够减少各个机种通用的四站装备数量需求,而单个机种特有的四站装备需求不变.