STUDY ON NEIGHBORHOOD DISCOVERY PROTOCOL IN COMMUNICATION NETWORKS

IntroductionIt is well known thatthe PNNIsystem is a de-veloping system in the private ATM networkfield[1～ 5] .According to Ref.[6],PNNI includestwo categories of protocols,one defines for dis-tributing topology information between switchesand clusters of switches- routing protocol,and theother defines the signalling- signalling protocol,which is message flows used to establish point topoint and point to multi- point connections acrossthe ATM network.Forrealizing the PNNIroutingwith m…     

跨境供应链网络海外仓的鲁棒性选址模型及算法

新经济形态下，全球政治、经济形势瞬息万变，多种人为和自然因素导致商业供应链的生存环境日益严峻. 跨境供应链网络作为典型的时效性和运营环境等都具有极大不确定性的复杂网络，研究其鲁棒性问题具有一定的理论意义和实际应用场景. 首先阐明了跨境供应链网络的内涵，认为海外仓的选址优化是控制网络鲁棒性的重要手段；随后基于最小最大后悔值构建了海外仓的鲁棒性选址模型，利用情景松弛算法对模型进行求解. 算例分析结果证明，所构建的海外仓鲁棒性选址模型及算法适用于跨境供应链网络情景.     

基于智能信号的动态路径选择模型研究

出行车辆的最优路径是随着时间和路况的变化而变化的，为了研究出行车辆的动态路径选择行为，基于有交通信号控制的交叉口，利用有向图理论，建立城市交通网络路径的优化模型，用传统dijkstra算法进行优化，动态获得出行车辆的最优路径。最后引入简单实例说明研究的方法，计算机仿真结果表明该方法是可行、有效的。     

Optimisation of nonlinear motion cueing algorithm based on genetic algorithm

Motion cueing algorithms (MCAs) are playing a significant role in driving simulators, aiming to deliver the most accurate human sensation to the simulator drivers compared with a real vehicle driver, without exceeding the physical limitations of the simulator. This paper provides the optimisation design of an MCA for a vehicle simulator, in order to find the most suitable washout algorithm parameters, while respecting all motion platform physical limitations, and minimising human perception error between real and simulator driver. One of the main limitations of the classical washout filters is that it is attuned by the worst-case scenario tuning method. This is based on trial and error, and is effected by driving and programmers experience, making this the most significant obstacle to full motion platform utilisation. This leads to inflexibility of the structure, production of false cues and makes the resulting simulator fail to suit all circumstances. In addition, the classical method does not take minimisation of human perception error and physical constraints into account. Production of motion cues and the impact of different parameters of classical washout filters on motion cues remain inaccessible for designers for this reason. The aim of this paper is to provide an optimisation method for tuning the MCA parameters, based on nonlinear filtering and genetic algorithms. This is done by taking vestibular sensation error into account between real and simulated cases, as well as main dynamic limitations, tilt coordination and correlation coefficient. Three additional compensatory linear blocks are integrated into the MCA, to be tuned in order to modify the performance of the filters successfully. The proposed optimised MCA is implemented in MATLAB/Simulink software packages. The results generated using the proposed method show increased performance in terms of human sensation, reference shape tracking and exploiting the platform more efficiently without reaching the motion limitations.     

Design of robust-stable and quadratic finite-horizon optimal controllers with low trajectory sensitivity for uncertain active suspension systems

This paper presents a design method for designing the robust-stable and quadratic-finite-horizon-optimal controllers of uncertain active suspension systems. The method integrates a robust stabilisability condition, the orthogonal functions approach (OFA) and the hybrid Taguchi-genetic algorithm (HTGA). Using the integrative computational method, a robust-stable and quadratic-finite-horizon-optimal controller with low-trajectory sensitivity can be obtained such that (i) the active suspension system with elemental parametric uncertainties is stabilised and (ii) a quadratic-finite-horizon-integral performance index including a quadratic trajectory sensitivity term for the nominal active suspension system is minimised. The robust stabilisability condition is proposed in terms of linear matrix inequalities (LMIs). Based on the OFA, an algebraic algorithm only involving the algebraic computation is derived for solving the nominal active suspension feedback dynamic equations. By using the OFA and the LMI-based robust stabilisability condition, the dynamic optimisation problem for the robust-stable and quadratic-finite-horizon-optimal controller design of the linear uncertain active suspension system is transformed into a static-constrained-optimisation problem represented by the algebraic equations with constraint of LMI-based robust stabilisability condition; thus greatly simplifies the design problem. Then, for the static-constrained-optimisation problem, the HTGA is employed to find the robust-stable and quadratic-finite-horizon-optimal controllers of the linear uncertain active suspension systems. A design example is given to demonstrate the applicability of the proposed integrative computational approach.     

预应力混凝土斜拉桥调索设计新方法

综合分析了当前各主要调索方法的流程及利弊后,指出了分阶段施工的悬臂浇筑预应力混凝土斜拉桥内力状态无法逼近一次合理成桥状态,进而提出预应力混凝土悬臂浇筑斜拉桥可不进行合理成桥状态分析,直接考虑施工阶段进行正装调索设计的新理念。     

Identification of nonlinear systems using modified particle swarm optimisation: a hydraulic suspension system

This paper presents a novel modified particle swarm optimisation (MPSO) algorithm to identify nonlinear systems. The case of study is a hydraulic suspension system with a complicated nonlinear model. One of the main goals of system identification is to design a model-based controller such as a nonlinear controller using the feedback linearisation. Once the model is identified, the found parameters may be used to design or tune the controller. We introduce a novel mutation mechanism to enhance the global search ability and increase the convergence speed. The MPSO is used to find the optimum values of parameters by minimising the fitness function. The performance of MPSO is compared with genetic algorithm and alternative particle swarm optimisation algorithms in parameter identification. The presented comparisons confirm the superiority of MPSO algorithm in terms of the convergence speed and the accuracy without the premature convergence problem. Furthermore, MPSO is improved to detect any changes of system parameters, which can be used for designing an adaptive controller. Simulation results show the success of the proposed algorithm in tracking time-varying parameters.     

Maximizing net benefits for conventional and flexible bus services

Transit ridership is usually sensitive to fares, travel times, waiting times, and access times, among other factors. Therefore, the elasticities of demand with respect to such factors should be considered in modeling bus transit services and must be considered when maximizing net benefits (i.e. “system welfare” = consumer surplus + producer surplus) rather just minimizing costs. In this paper welfare is maximized with elastic demand relations for both conventional (fixed route) and flexible-route services in systems with multiple dissimilar regions and periods. As maximum welfare formulations are usually too complex for exact solutions, they have only been used in a few studies focused on conventional transit services. This limitation is overcome here for both conventional and flexible transit services by using a Real Coded Genetic Algorithm to solve such mixed integer nonlinear welfare maximization problems with constraints on capacities and subsidies. The optimized variables include service type, zone sizes, headways and fares. We also determine the maximum welfare threshold between optimized conventional and flexible services) and explore the effects of subsidies. The proposed planning models should be useful in selecting the service type and optimizing other service characteristics based on local geographic characteristics and financial constraints.     

潜水器载人舱的不确定性测度计算方法研究

本文研究状态函数中存在概率数和证据数的混合状态下的系统不确定性分析方法问题,用于解决在产品实现过程中部分信息的认知不足。传统概率分析方法无法建立认知不确定信息模型,无法反映产品在实现过程中不确定性影响的问题。本文将证据理论不确定度分析方法融入传统JC算法,在计算随机变量迭代时开展认知变量极值计算,进而可以处理随机和认知不确定性变量同时存在时的混合不确定性问题。本文建立了4500 m载人潜水器载人舱不确定度分析模型,基于改进JC算法计算得到载人舱失效似然性测度和失效可信性测度值,同时采用实验设计法对影响载人舱不确定性测度的因素进行分析,分析表明测度影响较大的因素是真球度和极限拉伸强度,测度对真球度和厚度两个因素的单位数量变化比较敏感。     

基于遗传算法的盾构隧道管片接头刚度反演研究北大核心CSCD

梁-弹簧模型在管片衬砌结构计算中应用较广泛,目前接头刚度取值方法主要有模型试验法及经验取值法,模型试验法耗时长、成本高昂,而依据经验取值难免存在一定主观性。鉴于此,利用C++编程语言,基于遗传算法开发了盾构隧道管片结构位移反分析程序,首先通过弹性模量值反演算例,得出反演值与理论值误差为1.4%,验证了算法和程序的可行性。利用程序将反演接头刚度值与实际设计案例管片接头刚度值进行对比,反演计算结果表明:正弯矩下管片环向接头转动刚度值反演误差为2.6%,负弯矩下管片环向接头转动刚度值反演误差为4.3%。