基于双层博弈模型的民用航空产业链研究

本文针对民用航空市场中的大飞机制造商及航空发动机制造商建立双层博弈模型。在上层模型中,大飞机制造商以市场利润为目标决定其产量及对各发动机供应商的采购量;在下层模型中,航空发动机供应商通过求解一个优化问题决定其自身产量。在求解过程中,将下层优化问题转化为KKT条件,并作为上层优化问题的约束条件,使用分布式迭代算法(Distributed iterative algorithm),进行编程求解。本文通过求解波音-空客双寡头格局下的市场均衡对模型的有效性进行验证,并进一步分析国产大飞机C919量产后市场均衡的变化。     

乘用车物流运输计划问题的建模研究

首先针对不同类型、数量乘用车的物流运输问题,构建整数线性规划模型,并对模型进行逐层优化求解,通过MATLAB编写通用程序实现计算;在此基础之上,为解决不同目的地的运输要求,采用启发式逐层优化算法进行求解;最后考虑多因素的实际问题,建立分层划分模型,提出构造型分层划分启发式算法求解.计算表明,所建模型计算结果良好,实现了对乘用车物流运输计划问题的优化.     

工程建设企业多项目人力资源配置研究——基于胜任力和两阶段优化视角

主要研究工程建设企业多项目人力资源优化配置问题。以项目经理这一关键性人力资源为对象,构建了基于胜任力模型的工程建设企业项目经理能力定级指标体系,给出了具体的能级评价方法,解决了待分配人员的定级和排序问题;在项目优先级和人员能级界定的基础上,以多项目工期均衡和人工总成本最低为目标建立了两阶段优化模型,给出了基于贪婪算法和线性规划的模型求解算法,设计了MATLAB程序对模型进行求解;最后通过实例验证了优化配置模型和求解算法的有效性。     

基于CVaR的次优拥挤收费随机多目标模型北大核心

次优拥挤收费问题一般要考虑不同决策者的不同利益,因此,有必要考虑多个收费策略建立多目标模型来均衡不同决策者的利益.由于决策者常在信息不确定的情况下做决策,在出行需求不确定的条件下,为了确定次优拥挤收费的方案,建立了基于条件风险价值的随机多目标双层规划模型,上层规划的目标函数考虑了系统总阻抗和社会公平性,下层规划是UE用户均衡配流问题.利用基于随机模拟的遗传算法对模型进行求解,并通过数值算例对模型和算法进行分析,验证了模型的有效性.     

基于CVaR的次优拥挤收费随机多目标模型

次优拥挤收费问题一般要考虑不同决策者的不同利益,因此,有必要考虑多个收费策略建立多目标模型来均衡不同决策者的利益.由于决策者常在信息不确定的情况下做决策,在出行需求不确定的条件下,为了确定次优拥挤收费的方案,建立了基于条件风险价值的随机多目标双层规划模型,上层规划的目标函数考虑了系统总阻抗和社会公平性,下层规划是UE用户均衡配流问题.利用基于随机模拟的遗传算法对模型进行求解,并通过数值算例对模型和算法进行分析,验证了模型的有效性.     

面向节能的单/多列车优化决策问题

主要研究了单/多列车运行优化控制问题.首先建立了面向节能的单列车能耗优化模型,采用节能控制策略对模型进行求解,得出节能运行的速度距离曲线;其次对多列车多区段的节能运行进行优化控制设计,以再生能量利用最大化为目标,分别建立多列车能耗优化通用模型和高峰/非高峰情形下优化模型,利用模拟退火算法求解模型,得出使总能耗最低的列车运行方案;最后针对晚点情况下追踪运行的多列车运行优化控制问题,分别建立随机和非随机晚点情况下实时控制模型,求解得到耗能最少的列车运行曲线.     

邮政运输中邮路的规划和邮车调度问题的研究

以邮政运输网络中运输效益最优为目标,建立了分步规划的图论模型.运用Floyd算法、Kruskal算法对模型进行分步求解并逐步优化,通过Matlab、Lingo、SPSS软件求解,提出三种优化邮路、降低邮车调度成本的方法.模型对解决邮路问题、单旅行商、多旅行商等相关问题具有普遍适用性,可以推广到点数更多TSP的问题.     

基于IMO-SLFDA的大规模分布式光伏并网的智能配电网相位平衡研究

分布式光伏的大量接入智能配电网后,可能导致三相电流的失衡,进而破坏配电系统的安全稳定性。对此,本文构建了以电流不平衡和电能损失最小化为目标的含分布式光伏的配电网优化的多目标模型,旨在解决大规模分布式光伏发电并网后配电网相位平衡的问题;然后,用随机单纯形法对混合蛙跳算法进行优化,改进了蛙跳算法求解优化问题时极易陷入局部最优以及计算效率较低的缺点,并和决策算法相结合,提出适用本文算例的改进的多目标混合蛙跳决策算法,确保能以极快的搜索速度和较高的计算精度得到最优解;最后,以IEEE-123节点三相不平衡测试系统为例,通过控制变量的相关操作实现配电系统的三相平衡。对比分析基础案例和优化算例的差异,验证了本文所提算法的先进性和实用性。     

军需物资调集规划问题的研究

以军需物资调集为背景 ,在系统分析的基础上建立了全局优化问题的数学规划模型 ,并对模型求解进行了研究 ,提出两阶段规划算法 .仿真计算结果表明所建模型的有效性     

考虑服务水平的逆向物流网络优化决策

针对电子产品的售后维修服务问题,建立了一个同时考虑成本和服务质量的多目标逆向物流网络优化模型;该问题是多目标的NP-hard问题,应用NSGA-II算法和多目标模拟退火算法(MOSA)两种多目标进化算法,对模型进行求解并对其求解的效果进行比较分析;多组算例测试结果表明,NSGA-II相比MOSA更具优势。     

Web server load balancing: A queueing analysis

Over the last few years, the Web-based services, more specifically different types of E-Commerce applications, have become quite popular, resulting in exponential growth in the Web traffic. In many situations, this has led to unacceptable response times and unavailability of services, thereby driving away customers. Many companies are trying to address this problem using multiple Web servers with a front-end load balancer. Load balancing has been found to provide an effective and scalable way of managing the ever-increasing Web traffic. However, there has been little attempt to analyze the performance characteristics of a system that uses a load balancer. This paper presents a queuing model for analyzing load balancing with two Web servers. We first analyze the centralized load balancing model, derive the average response time and the rejection rate, and compare three different routing policies at the load balancer. We then extend our analysis to the distributed load balancing and find the optimal routing policy that minimizes the average response time.     

大规模系统的全局优化

本文讨论了可分非凸大规模系统的全局优化控制问题 .提出了一种 3级递阶优化算法 .该算法首先把原问题转化为可分的多目标优化问题 ,然后凸化非劣前沿 ,再从非劣解集中挑出原问题的全局最优解 .建立了算法的理论基础 ,证明了算法的收敛性 .仿真结果表明算法是有效的 .     

Simultaneous determination of capacities and load in parallel M/M/1 queues

In this paper, we address an analytical model to simultaneously determine the processing capacity and load assigned to each processor in a multiple processor configuration within the framework of M/M/1 queues. A queueing optimization model is formulated as a nonlinear programming problem having linear constraints. We then propose an optimization algorithm that utilizes the special structure of the problem. To illustrate the applicability of our method, a small sample system has been solved.     

负载均衡问题

自Ron Graham20世纪60年代发表第一篇负载均衡算法的论文以来,平行机排序作为组合优化近似算法理论的首个问题引起了学界的广泛兴趣,其本身研究的不断深化也一路见证了该领域的发展历程.介绍负载均衡问题的来龙去脉,特别是作者所在团队在相关问题的研究进展,从算法和复杂性不同的视角分析经典问题的计算本质,并对未来的研究提出一些建议.     

On the multi-component layout design with inertial force

The purpose of this paper is to introduce inertial forces into the proposed integrated layout optimization method designing the multi-component systems. Considering a complex packing system for which several components will be placed in a container of specific shape, the aim of the design procedure is to find the optimal location and orientation of each component, as well as the configuration of the structure that supports and interconnects the components. On the one hand, the Finite-circle Method (FCM) is used to avoid the components overlaps, and also overlaps between components and the design domain boundaries. One the other hand, the optimal material layout of the supporting structure in the design domain is designed by topology optimization. A consistent material interpolation scheme between element stiffness and inertial load is presented to avoid the singularity of localized deformation due to the presence of design dependent inertial loading when the element stiffness and the involved inertial load are weakened with the element material removal. The tested numerical example shows the proposed methods extend the actual concept of topology optimization and are efficient to generate reasonable design patterns.     

Load balancing optimization of telecommunication networks with two differentiated services

The Differentiated Services architecture is a scalable solution to provide differentiated Quality of Service. In this paper, we address the network load balancing optimization of such networks based on bandwidth differentiation between two services. We define the optimization problem as an Integer Programming model and propose a heuristic algorithm based on GRASP with Path Relinking. We present computational results showing that (i) good quality solutions can be computed and (ii) proper load balancing can efficiently obtain service differentiation.     

A hybrid metaheuritic technique developed for hourly load forecasting

Electricity load forecasting has become one of the most functioning tools in energy efficiency and load management and utility companies which has been made very complex due to deregulation. Due to the importance of providing a secure and economic electricty for the consumers, having a reliable and robust enough forecast engine in short‐term load management is very needful. Fuzzy inference system is one of primal branches of Artificial Intelligence techniques which has been widely used for different applications of decision making in complex systems. This paper aims to develop a Fuzzy inference system as a main forecast engine for Short term Load Forecasting (STLF) of a city in Iran. However, the optimization of this platform for this special case remains a basic problem. Hence, to address this issue, the Radial Movement Optimization (RMO) technique is proposed to optimize the whole Fuzzy platform. To support this idea, the accuracy of the proposed model is analyzed using MAPE index and an average error of 1.38% is obtained for the forecast load demand which represents the reliability of the proposed method. Finally, results achieved by this method, demonstrate that an adaptive two‐stage hybrid system consisting of Fuzzy & RMO can be an accurate and robust enough choice for STLF problems. © 2016 Wiley Periodicals, Inc. Complexity 21: 521–532, 2016     

Optimal discrete long-term operation of nuclear-hydrothermal power systems

We discuss in this paper an algorithm for solving the optimal long-term operating problem of a hydrothermal-nuclear power system by application of the minimum norm optimization technique. The algorithm proposed here has the ability to deal with large-scale power systems and with equality and/or inequality constraints on the variables. A discrete model for the xenon and iodine concentrations is used, as well as a discrete model for hydro reservoirs. The optimization is done on a monthly time basis. For simplicity of the problem formulation, the transmission line losses are considered as a part of the load.This work supported by the Natural Sciences and Engineering Research Council of Canada, Grant No. A4146.     

计及需求响应不确定性的综合能源系统多目标优化调度管理

需求响应作为电力系统的重要调节手段,可显著提升系统灵活性和经济性。利用价格弹性构建了包含价格与激励措施的需求响应模型,并在此基础上考虑需求响应的不确定性,以综合能源系统经济性和环保性为优化目标,构建了综合能源系统多目标优化调度模型。利用E约束法将多目标优化模型转化为单目标优化模型,得到Pareto最优解集,运用模糊决策法从中选取最优方案。基于实际案例进行测算,结果表明价格型与激励型需求响应手段的结合能够实现削峰填谷,有效降低系统的运行成本和碳排放量。     

An Exact Solution Method for Reliability Optimization in Complex Systems

Systems reliability plays an important role in systems design, operation and management. Systems reliability can be improved by adding redundant components or increasing the reliability levels of subsystems. Determination of the optimal amount of redundancy and reliability levels among various subsystems under limited resource constraints leads to a mixed-integer nonlinear programming problem. The continuous relaxation of this problem in a complex system is a nonconvex nonseparable optimization problem with certain monotone properties. In this paper, we propose a convexification method to solve this class of continuous relaxation problems. Combined with a branch-and-bound method, our solution scheme provides an efficient way to find an exact optimal solution to integer reliability optimization in complex systems. This research was partially supported by the Research Grants Council of Hong Kong, grants CUHK4056/98E, CUHK4214/01E and 2050252, and the National Natural Science Foundation of China under Grants 79970107 and 10271073.