电网安全调度中输电阻塞管理的演化策略

输电阻塞是电力系统运行中的常见问题 .本文建立了用于电网安全调度中输电阻塞管理的数学模型——带线性约束的多目标模糊优化问题模型 ,给出了求解该模型的演化策略 .实际的计算结果表明 ,演化策略解决输电阻塞问题是有效的 .     

Single-path routing of stochastic flows in networks

The paper revisits a very simple network routing and dimensioning model, with two specific assumptions: the traffic amounts to be routed are Gaussian random variables, and each commodity must use one single route in the network. The need to control congestion leads naturally to probabilistic constraints. The impact of stochastic assumptions on solution algorithms is investigated, when compared to the usual deterministic case.     

考虑路网可靠性和空间公平性的次优拥挤收费模型

根据随机路网环境下出行者规避风险的路径选择行为,提出了一种考虑路网可靠性和空间公平性的次优拥挤收费双层规划模型。其中,上层模型以具有空间公平性约束条件下最大化路网的社会福利为目标,下层模型是实施拥挤收费条件下考虑行程时间可靠性的弹性需求用户平衡模型。鉴于双层规划模型的复杂性,设计了基于遗传算法和FrankWolfe算法的组合式算法来求解提出的模型。算例结果表明:考虑行程时间可靠性的次优拥挤收费会产生不同于传统次优拥挤收费的平衡流量分布模式,表明出行者的路径选择行为对拥挤收费结果会产生直接影响;此外,算例结果还说明遗传算法对参数设置具有很强的鲁棒性。     

基于厌恶行为的冷链网络优化问题的研究

客户对冷链产品新鲜度的要求越来越高,但随着时间的变化,冷链产品品质在逐渐下降,客户的心理也在相应变化。在考虑交通阻塞的情况下,本文构建了客户厌恶行为函数,同时根据配送过程对车辆和驾驶员的被占用时间构建了配送中心厌恶行为函数,通过分配不同的权重将两个厌恶行为函数结合起来,在一系列约束条件下,以整体厌恶行为最小和成本最小为目标函数,建立了相应的数学模型。最后使用算例进行仿真,验证了所建立的数学模型是可行的。     

Irregular trajectories in vakonomic mechanical systems

In his works, V.V. Kozlov proposed a mathematical model for the dynamics of a mechanical system with nonintegrable constraints, which was called vakonomic. In contrast to the then conventional nonholonomic model, trajectories in the vakonomic model satisfy necessary conditions for a minimum in a variational problem with equality constraints. We consider the so-called irregular case of this variational problem, which was not covered by Kozlov, when the trajectory is a singular point of the constraints and the necessary minimum conditions based on the Lagrange principle make no sense. This situation is studied using the theory of abnormal problems developed by the first author. As a result, the classical necessary minimum conditions are strengthened and developed to this class of problems.     

An interior-point approach for primal block-angular problems

Multicommodity flows belong to the class of primal block-angular problems. An efficient interior-point method has already been developed for linear and quadratic network optimization problems. It solved normal equations, using sparse Cholesky factorizations for diagonal blocks, and a preconditioned conjugate gradient for linking constraints. In this work we extend this procedure, showing that the preconditioner initially developed for multicommodity flows applies to any primal block-angular problem, although its efficiency depends on each particular linking constraints structure. We discuss the conditions under which the preconditioner is effective. The procedure is implemented in a user-friendly package in the MATLAB environment. Computational results are reported for four primal block-angular problems: multicommodity flows, nonoriented multicommodity flows, minimum-distance controlled tabular adjustment for statistical data protection, and the minimum congestion problem. The results show that this procedure holds great potential for solving large primal-block angular problems efficiently.     

A mixed-integer programming approach to a class timetabling problem: A case study with gender policies and traffic considerations

This paper considers the class scheduling and timetabling problem faced at Kuwait University (KU). The principal focus is to design efficient class offering patterns while taking into consideration newly imposed gender policies. We formulate a mathematical programming model that assigns offered classes to time-slots and addresses gender issues by defining appropriate surrogate constraints along with objective penalty terms. The model aims to enhance existing manual scheduling and timetabling approaches that are often accompanied with arduous combinatorial tasks such as resolving class conflicts, dealing with parking and traffic congestion, and ensuring an efficient utilization of facility and human resources. This modeling approach emphasizes the generation of flexible class timetables for students, and the efficient utilization of available facility resources. Computational results based on a number of case studies related to Kuwait University reveal that this approach yields improved schedules in terms of offering patterns and class conflicts.     

The effect of information on commuters' behavior: A comparative micro-simulation approach

This paper presents a micro simulation model for studying the effect of information on commuters' behavior during morning peak congestion, and its impact is examined here in relation to network performance. The model is fed by survey data of perceived behavior in two cities in two different countries: Israel and Sweden. The model considers parameters such as: home-to-work trips, constraints with respect to the arrival time at the destination, exposure to various levels of information, flexibility of the mode of transportation, pre-trip information and en-route information.     

基于线路“异质性”假设的轴辐式公共交通网络优化研究

特大城市公共交通局部静态拥堵问题日益成为制约公共交通网络运行效率提高的关键。针对这一问题改变线路“同质性”假设,在线路“异质性”假设的基础上,提出了将轴辐式网络设计运用到公共交通领域中来,综合考虑居民采用公共交通方式出行的单位运输可变成本、不变成本、枢纽换乘成本等要素,将枢纽间大型客车干线运输所带来的规模经济效应进行量化,构建了基于单分配、多枢纽、混合式网络结构特征的轴辐式公共交通网络优化模型,旨在多重约束下通过枢纽布局降低网络运输成本,提高公共交通网络站点的可达性。最后根据模拟退火算法对模型进行求解,并通过算例分析与讨论的方式验证了模型的有效性。     

Passenger flow control strategies for urban rail transit networks

Urban rail traffic congestion is becoming increasingly serious due to the large traffic demands in modern cities. In order to ensure the safety and quality of station services in peak hours, it's necessary to adopt some reasonable and effective passenger flow control strategies. In this study, through considering the time-dependent passenger demands, a passenger flow control model based on the network-level system is explicitly developed. The passenger successive motion process is discretized by the modeling method. Systematically considering the coordinated relationship between traffic demands and strict capacity constraints (including station passing capacity, platform load capacity and train transport capacity), we establish a mixed integer linear programming model to minimize the total passenger waiting time (including passengers outside stations and on the platforms). The optimization software Cplex is adopted to solve the developed model, and a real network of Beijing urban railway is calibrated to verify the effectiveness of the suggested model. As a result, the proposed flow control strategies can provide detailed information about control stations, control durations and control intensities, and can effectively reduce the total waiting time and relieve the number of stranded passengers in the urban rail transit network.     

Solving the minimum toll revenue problem in real transportation networks

As a means to relieve traffic congestion, toll pricing has recently received significant attention by transportation planners. Inappropriate use of transportation networks is one of the major causes of network congestion. Toll pricing is a method of traffic management in which traffic flow is guided to proper time and path in order to reduce the total delay in the network. This article investigates a method for solving the minimum toll revenue problem in real and large-scale transportation networks. The objective of this problem is to find link tolls that simultaneously cause users to efficiently use the transportation network and to minimize the total toll revenues to be collected. Although this model is linear, excessive number of variables and constraints make it very difficult to solve for large-scale networks. In this paper, a path-generation algorithm is proposed for solving the model. Implementation of this algorithm for different networks indicates that this method can achieve the optimal solution after a few iterations and a proper CPU time.     

Mathematics education: Procedures, rituals and man's search for meaning

An attempt is made to analyze mathematical behavior from more general psychological perspectives. The mathematical language is a special case of the human language, which is a form of expression. Many people use common language in a meaningless way. The same is true about the mathematical language. Rituals are other forms of expression. Many people identify rituals in many mathematical contexts (procedures, argumentation). Thus, quite often, they behave in a meaningless way as required by many rituals. On the other hand, the community of mathematics education struggles for meaningful learning. This can be regarded as a special case of man's search for meaning. The general claims will be illustrated by some examples from various mathematical contexts.     

Homotopy theory of simplicial sheaves in completely decomposable topologies

There are two approaches to the homotopy theory of simplicial (pre-)sheaves. One developed by Joyal and Jardine works for all sites but produces a model structure which is not finitely generated even in the case of sheaves on a Noetherian topological space. The other one developed by Brown and Gersten gives a nice model structure for sheaves on a Noetherian space of finite dimension but does not extend to all sites. In this paper we define a class of sites for which a generalized version of the Brown-Gersten approach works.     

Probabilistic programming models for traffic incident management operations planning

This paper proposes mathematical programming models with probabilistic constraints in order to address incident response and resource allocation problems for the planning of traffic incident management operations. For the incident response planning, we use the concept of quality of service during a potential incident to give the decision-maker the flexibility to determine the optimal policy in response to various possible situations. An integer programming model with probabilistic constraints is also proposed to address the incident response problem with stochastic resource requirements at the sites of incidents. For the resource allocation planning, we introduce a mathematical model to determine the number of service vehicles allocated to each depot to meet the resource requirements of the incidents by taking into account the stochastic nature of the resource requirement and incident occurrence probabilities. A detailed case study for the incident resource allocation problem is included to demonstrate the use of proposed model in a real-world context. The paper concludes with a summary of results and recommendations for future research.     

A two-server queueing system with periodic and credit-based server availabilities

A discrete-time, two-server queueing system is studied in this paper. The service time of a customer (cell) is fixed and equal to one time unit. Server 1 provides for periodic service of the queue (periodT). Server 2 provides for service only when server 1 is unavailable and provided that the associated service credit is nonzero. The resulting system is shown to model the queueing behavior of a network user which is subject to traffic regulation for congestion avoidance in high speed ATM networks. A general methodology is developed for the study of this queueing system, based on renewal theory. The dimensionality of the developed model is independent ofT;T increases with the network speed. The cell loss probabilities are computed in the case of finite capacity queue.Research supported by the National Science Foundation under grant NCR-9011962.     

Mathematical Analysis of a Chemotaxis-Type Model of Soil Carbon Dynamic

The goal of this paper is to study the mathematical properties of a new model of soil carbon dynamics which is a reaction-diffusion system with a chemotactic term, with the aim to account for the formation of soil aggregations in the bacterial and microorganism spatial organization (hot spot in soil). This is a spatial and chemotactic version of MOMOS (Modelling Organic changes by Micro-Organisms of Soil), a model recently introduced by M. Pansu and his group. The authors present here two forms of chemotactic terms, first a “classical” one and second a function which prevents the overcrowding of microorganisms. They prove in each case the existence of a nonnegative global solution, and investigate its uniqueness and the existence of a global attractor for all the solutions.     

考虑翻箱的场桥调度和提箱集卡数量的集成优化

在集装箱码头的进口箱堆场中,码头预约机制、待提箱的实时位置和场桥作业调度方案是制约堆场作业效率和堵塞情况的关键。为缓解进口箱堆场的拥塞情况并提高作业效率,在固定的预约时段内,考虑实时压箱量最少的翻箱规则,兼顾场桥间不可跨越和保持安全间距等现实约束,以场桥最长完工时间最小为目标,构建数学优化模型,设计了嵌入修复算子的改进遗传算法用于求解;通过算例实验验证了算法的有效性和方案的优越性,可为堆场实际作业提供决策参考。     

Optimal budget for system design series network DEA model

Wei and Chang (2011a) developed optimal system design (OSD) data envelopment analysis (DEA) models to design a decision-making unit (DMU)’s optimal system, in which the DMU could encounter the well-known economic phenomenon of budget congestion. To show how to verify the optimal budget and budget congestion, they develop a solution method. In this paper, we note that their method is incorrect for the OSD network DEA model in general. A new approach is developed to derive the DMU’s corresponding optimal budgets and to check for the existence of budget congestion not only for the OSD DEA models but also for the OSD network DEA models. In addition, the proposed approach is computationally economical. Finally, two numerical examples are used to illustrate the proposed approach.     

Global Solution Approach for a Nonconvex MINLP Problem in Product Portfolio Optimization

The rigorous and efficient determination of the global solution of a nonconvex MINLP problem arising from product portfolio optimization introduced by Kallrath (2003) is addressed. The objective of the optimization problem is to determine the optimal number and capacity of reactors satisfying the demand and leading to a minimal total cost. Based on the model developed by Kallrath (2003), an improved formulation is proposed, which consists of a concave objective function and linear constraints with binary and continuous variables. A variety of techniques are developed to tighten the model and accelerate the convergence to the optimal solution. A customized branch and bound approach that exploits the special mathematical structure is proposed to solve the model to global optimality. Computational results for two case studies are presented. In both case studies, the global solutions are obtained and proved optimal very efficiently in contrast to available commercial MINLP solvers.     

A light-propagation model for aircraft trajectory planning

Predicted air traffic growth is expected to double the number of flights over the next 20 years. If current means of air traffic control are maintained, airspace capacity will reach its limits. The need for increasing airspace capacity motivates improved aircraft trajectory planning in 4D (space+time). In order to generate sets of conflict-free 4D trajectories, we introduce a new nature-inspired algorithm: the light propagation algorithm (LPA). This algorithm is a wavefront propagation method that yields approximate geodesic solutions (minimal-in-time solutions) for the path planning problem, in the particular case of air-traffic congestion. In simulations, LPA yields encouraging results on real-world traffic over France while satisfying the specific constraints in air-traffic management.