Optimization Design of Holding Poles Based on the Response Surface Methodology and the Improved Arithmetic Optimization Algorithm北大核心CSCD

抱杆优化设计需要耗费大量有限元分析计算时间,难以确定可行域.该文采用响应面法(response surface method,RSM)来模拟抱杆结构的真实响应,提出了改进的算术优化算法(improved arithmetic optimization algorithm,IAOA)对抱杆结构进行优化设计.将分数阶积分引入算术优化算法(arithmetic optimization algorithm,AOA),改善了算法的开发能力.采用拉丁超立方抽样,选取抱杆结构杆件截面试验样本,利用最小二乘法对样本点进行分析,构建了抱杆结构应力和位移关于杆件截面尺寸的二阶响应面代理模型.建立以抱杆质量最小化为优化目标,许用应力和位移为约束条件的优化模型,采用IAOA对其进行求解.结果表明:二阶响应面模型能够准确预测抱杆结构的响应值,IAOA的求解精度得到显著提升,代理模型可大幅降低有限元分析所需的计算代价,优化后抱杆结构质量减轻了8.2%.联合使用RSM和IAOA可有效求解大型空间杆系结构的优化设计问题.     

计算流体力学在大型风力机空气动力学的应用进展北大核心CSCD

针对大型风力机设计中的关键空气动力学问题,比较系统地介绍了计算流体力学(computational fluid dynamics,CFD)方法的主要应用,特别是在大型风力机翼型气动分析、风力机流动的数值模拟、风轮空气动力特性的数值计算以及大型风力机叶片的多目标气动优化设计方面的进展.基于CFD方法分别实现了风力机翼型与叶片二维/三维气动特性的准确预测,风力机尾流场涡系结构的准确捕捉;并结合多目标遗传算法对1.5 MW风力机叶片进行了优化,获得了具有高风能利用效率的叶片方案.     

改进的NSGA-Ⅱ算法研究风力机叶片多目标优化

将一种采用精英控制策略和动态拥挤方法用于快速非支配排序遗传算法（NSGA-Ⅱ）,并应用到风力机叶片的优化研究中,获得了一种新颖的风力机叶片多目标优化设计方法．作为应用算例,以设计风速下的功率系数最大和叶片质量最小为优化目标,用该方法设计了5 MW大型风力机叶片．优化结果表明,此算法在处理风力机多目标优化问题取得了良好的效果,给出的是一个Pareto最优解集,而不是传统优化方法追求的单个最优解,为风力机多目标优化设计提供新的思路和通用的算法．     

基于自适应萤火虫算法的液压缸优化设计

针对液压缸优化设计问题,以液压机法兰支承液压缸为应用背景,在ANSYS软件中对液压缸进行有限元分析.建立以液压缸体积最小为优化目标的优化数学模型,提出一种自适应萤火虫算法求解模型对液压缸的结构参数进行优化.仿真结果表明,所提出自适应萤火虫算法比基本萤火虫算法收敛的精度更高,迭代次数更少,优化后液压缸的体积相对减少了42.3%,较好地解决了液压缸优化设计问题.进一步对优化后的油缸进行了有限元分析,验证了优化结果的正确性.     

具有动应力、位移和稳定性约束的离散变量桁架结构布局优化设计算法

给出了在动应力、动位移和动稳定约束下离散变量结构布局优化设计问题的数学模型,用“拟静力”算法,将具有动应力约束、动位移约束和动稳定约束的离散变量结构布局优化设计问题化为静应力、静位移和静稳定约束的优化问题,然后利用两级优化算法求解该模型．优化过程由两级组成,拓扑级优化和形状级优化．在每一级,都使用了综合算法,并且在搜索过程中都根据两类设计变量的相对差商值进行搜索．对包含稳定约束和不包含稳定约束的优化结果做了比较,结果显示稳定性约束对优化结果产生较大的影响．     

多目的地多停车场系统动态停车分配模型

在一个多目的地多停车场系统中,每个目的地附近有多个停车场可供选择,每个停车场也可供多个目的地的停车需求停车。每个目的地的停车需求在各停车场的停车量即为停车分配问题. 本文定义了停车量分配均衡原则:各目的地的驾驶员总是首选最低费用(包括在停车场内的停车费用以及停车时间、步行时间转换后的货币成本,其中停车费用及在停车场内的车位找寻时间都正相关于该停车场当前时刻停车饱和度)的停车场停车;由于停车场具有容量限制,当费用最低的停车场已满则再选择费用次低的停车场,以此类推;所有没被使用的停车场或者比被使用的停车场具有更高的费用或者停车位已满。考虑停车需求和各停车场内空余泊位数的实时动态特性,提出了与该均衡原则等价的数学规划模型,证明了其解的唯一性并设计了求解算法。通过两个算例对模型进行了验证,并再现了目的地附近各停车场内车位占用变化规律,从而为动态停车收费、停车选址规划等提供依据。     

面向不同占用率水平的泊位共享动态定价策略

为了满足停车场多方利益需求,实现区域内泊位占用率均衡的目标,提出了面向不同泊位占用率水平的动态定价策略.基于车主停车行为特征测算泊位综合效用及车主选择泊位概率,在预测停车场泊位需求的基础上构建定价模型,确定了区域内不同占用率水平下的目标函数,最终引入遗传算法进行优化求解.结果表明:利用构建的动态定价模型能够有效调整区域内泊位占用率水平,实现不同水平下的多方利益最大化,提高社会效益.     

基于粒子群算法的大型网络计划资源优化

现有求解网络计划资源优化的方法中,解析法不能解决大型复杂网络优化问题,启发式方法过多依赖具体问题、求解效率低,遗传算法生成新一代优化解种群依据的三个算子的实现参数选择,大部分依靠经验并严重影响解的品质,粒子群算法存在大型网络计划资源优化计算量过大和缺少大型网络计划资源优化算例问题.借助设计网络计划时间参数的计算机算法、建立评价函数、设计进化方程等基础工作,选择与工作开始时间相关的变量作为粒子空间位置,用蒙特卡洛方法和限制条件优化初始粒子群,设置可行解范围,用二维动态数组解决大型网络计划资源优化运行image超限问题,通过粒子群算法进化,寻求大型网络计划资源优化解,算例表明基于粒子群算法的大型网络计划资源优化效果明显,粒子群算法参数分析表明:粒子群算法的参数会影响网络计划资源优化结果,而且初始粒子群限制条件和优化目标设置的影响程度较大.     

利用遗传算法对生物质发电集料处理系统优化研究

遗传算法是一种基于生物选择与遗传机理的随机搜索与优化的方法,近年来解决了许多不同领域不同类型的优化难题.采用此方法就生物质发电过程中集料处理作业系统优化问题进行了研究.文中以获取最小生物质发电集料处理系统成本为目标,利用遗传算法对集料处理系统工序进行了优化设计,通过输入实际案例数据,得到的输出结果与试验结果一致,证明了设计的有效性.同时,通过测试不同参数取值对输出结果的影响,得到了最佳参数值.研究对于企业优化生产工艺、降低生产成本,对于政府审核生物质发电项目具有重大意义.     

城市垃圾收运系统中的车辆收运计划问题

将垃圾收运系统中收运小车一天的收运计划问题,分为停车场设在转运站或别处两种情况,以小车行走总距离最小为目标,分别构建了混合整数规划模型.接着提出问题的求解思路:当停车场设在转运站时,可以将问题转化为VRP问题求解;若停车场设在别处,在求解上一问题的基础上设计了最近回路节点插入法将停车场插入离其最近的回路节点即可.最后以实例验证了模型和求解思路的可行性和有效性.     

Admission and pricing optimization of on-street parking with delivery bays

We analyze a parking lot, modeled as a loss queue, with passenger and delivery vehicles. The arrival process of delivery vehicles is exogenous, while that of passenger vehicles is a function of the parking price rate and accessibility. The aim of the parking operator is to maximize the revenue generated from passenger vehicles while providing a sufficient service level for delivery vehicles, in terms of their probability to find an available parking spot. Two levels of control are exercised: pricing and admission. From a Markov decision process approach, we prove that the optimal policy is a state-dependent reservation threshold policy that randomizes in at most one state. When some parking spots should be reserved for delivery vehicles, the price rate is selected to saturate the service level constraint, whereas when it is optimal not to restrict the parking lot accessibility, the price can also be selected as the unique local maximum of the revenue or to incentivize all potential passenger vehicles to arrive. Pricing should be used as a primary tool to control the flow of passenger vehicles. In complement, admission control is exercised with a limited use of reservation only when the service level guarantee for delivery vehicles is high.     

Congestion in large balanced multirate networks

In this paper, we obtain analytical approximations for various performance measures for a large fluid stochastic network that operates under a balanced fair bandwidth allocation policy. Balanced fairness results in the insensitivity of the stationary distribution of the number in the system to the precise distribution of file sizes. Balanced fairness has been shown to coincide with proportional fairness in large systems. The model we consider is that of servers operating under balanced fair rate allocations that are accessed by a large number of independent heterogeneous flows characterized by their arrival rate and general distributions of the file sizes; and a maximum service rate associated with each type of flow. The largeness of the system is parameterized by a scaling parameter that scales the arrival rates and capacity in such a way that the ratio is fixed. By exploiting a connection of the congestion probabilities with multirate Erlang loss systems, we use local limit large deviation methods to obtain accurate approximations as the scaling increases. The paper first discusses the single link case which is then extended to the case of a parking lot model that is a special case of tree networks.     

Optimal solutions for a dock assignment problem with trailer transportation

This paper presents a model for a dock assignment problem, where trailers need to be assigned to gates for a given period of time for loading or unloading activities. The parking lot is used as a buffer zone. Transportation between the parking lot and the gates is performed by additional resources called terminal tractors. The problem is modeled as a three-stage flexible flow shop, where the first and the third stage share the same identical parallel machines and the second stage consists of a different set of identical parallel machines. We examine multiple integer-programming formulations for the parallel-machine model in stage two and for the three-stage flow shop and we provide extensive computational results. Our goal is to explore the limits of the instance sizes that can be solved to guaranteed optimality within acceptable running times using integer programming.     

Two-boundary lattice paths and parking functions

We describe an involution on a set of sequences associated with lattice paths with north or east steps constrained to lie between two arbitrary boundaries. This involution yields recursions (from which determinantal formulas can be derived) for the number and area enumerator of such paths. An analogous involution can be defined for parking functions with arbitrary lower and upper bounds. From this involution, we obtained determinantal formulas for the number and sum enumerator of such parking functions. For parking functions, there is an alternate combinatorial inclusion–exclusion approach. The recursions also yield Appell relations. In certain special cases, these Appell relations can be converted into rational or algebraic generating functions.     

遗传算法在自动泊车辅助系统模糊控制中的应用

随着汽车工业的发展,自动泊车辅助系统已逐渐成为汽车的必备装置.对自动泊车控制过程进行了分析,设计了自动泊车辅助系统模糊控制器,并将遗传算法应用于模糊控制器参数寻优过程,较为有效的确定了模糊控制器的参数,使用遗传算法工具箱对模糊控制器的隶属度函数进行了优化.并在Matlab环境下,对自动泊车模糊控制进行了仿真研究,论述了遗传算法在改善模糊控制效果中的应用.     

Parking Capacity and Pricing in Park'n Ride Trips: A Continuous Equilibrium Network Design Problem

In this paper we consider the problem of designing parking facilities for park'n ride trips. We present a new continuous equilibrium network design problem to decide the capacity and fare of these parking lots at a tactical level. We assume that the parking facilities have already been located and other topological decisions have already been taken.The modeling approach proposed is mathematical programming with equilibrium constraints. In the outer optimization problem, a central Authority evaluates the performance of the transport network for each network design decision. In the inner problem a multimodal traffic assignment with combined modes, formulated as a variational inequality problem, generates the share demand for modes of transportation, and for parking facilities as a function of the design variables of the parking lots. The objective is to make optimal parking investment and pricing decisions in order to minimize the total travel cost in a subnetwork of the multimodal transportation system.We present a new development in model formulation based on the use of generalized parking link cost as a design variable.The bilevel model is solved by a simulated annealing algorithm applied to the continuous and non-negative design decision variables. Numerical tests are reported in order to illustrate the use of the model, and the ability of the approach to solve applications of moderate size.     

A mathematical model and algorithms for the aircraft hangar maintenance scheduling problem

An aircraft hangar maintenance scheduling problem is studied, motivated by the aircraft heavy maintenance conducted in a hangar operated by an independent maintenance service company. The aircraft hangar maintenance scheduling problem in such context consists of determining a maintenance schedule with minimum penalty costs in fulfilling maintenance requests, and a series of hangar parking plans aligned with the maintenance schedule through the planning period. A mixed-integer linear programming (MILP) mathematical model, integrating the interrelations between the maintenance schedule and aircraft parking layout plans, is presented at first. In the model, the variation of parking capacity of the maintenance hangar and the blocking of the aircraft rolling in and out path are considered. Secondly, the model is enhanced by narrowing down the domain of the time-related decision variables to the possible rolling in and out operations time of each maintenance request. Thirdly, to obtain good quality feasible solutions for large scale instances, a rolling horizon approach incorporating the enhanced mathematical model is presented. The results of computational experiments are reported, showing: (i) the effectiveness of the event-based discrete time MILP model and (ii) the scalability of the rolling horizon approach that is able to provide good feasible solutions for large size instances covering a long planning period.     

Sojourn time asymptotics in a parking lot network

For a two-class two-node bandwidth sharing network called parking lot network we investigate the tail behavior of the queue length and sojourn time under light-tailed assumptions. These results extend previous results in the literature obtained for a single-node network. Explicit conditions are given that indicate whether congestion at the second node influences the large deviations behavior or not. To overcome the complexities that arise when moving away from the single node case, we rely on recent results on overloaded bandwidth sharing networks obtained by Borst et al. (2009), and a comparison with the modified proportional fairness discipline, as introduced by Massoulié (Ann Appl Probab 17: 809–839, 2007). Specifically, our results include upper bounds for the distribution of the number of flows in the network, finiteness of the moment generating function of the workload, and large-deviations asymptotics for the sojourn time assuming flow size distributions having a bounded hazard rate.