Modified origin-based algorithm for traffic equilibrium assignment problems

Key tactics of origin-based user equilibrium (OUE) algorithm was studied,which involved the algorithm procedure and several implementation issues.To speed up the convergence,update policies of flows,costs and bushes were proposed.The methods of step-size searching and bush construction are proved to be practical.The modified OUE algorithm procedure was also optimized to take the advantage of multi-thread process.Convergence performances were compared with those of other algorithms by different sizes of urban transportation networks.The result shows this modified OUE algorithm is more efficient and consumes less time to achieve the reasonable relative gap in practical applications.

Real Time Equilibrium Reconstruction Algorithm in EAST Tokamak

The EAST (HT-7U) superconducting tokamak is a national project of China on fusion research, with a capability of long-pulse (- 1000 s) operation. In order to realize a long-duration steady-state operation of EAST, some significant capability of real-time control is re-quired. It would be very crucial to obtain the current profile parameters and the plasma shapes in real time by a flexible control system. As those discharge parameters cannot be directly measured, so a current profile consistent with the magnetohydrodynamic equilibrium should be evaluated from external magnetic measurements, based on a linearized iterative least square method, which can meet the requirements of the measurements. The arithmetic that the EFIT (equilibrium fitting code) is used for reference will be given in this paper and the computational efforts are reduced by parametrizing the current profile linearly in terms of a number of physical parameters. In order to introduce this reconstruction algorithm clearly, the main hardware design will be listed also.

An Algorithm for Traffic Equilibrium Flow with Capacity Constraints of Arcs

In the traffic equilibrium problem, we introduce capacity constraints of arcs, extend Beckmann’s formula to include these constraints, and give an algorithm for traffic equilibrium flows with capacity constraints on arcs. Using an example, we illustrate the application of the algorithm and show that Beckmann’s formula is a sufficient condition only, not a necessary condition, for traffic equilibrium with capacity constraints of arcs.

Modified stochastic user-equilibrium assignment algorithm for urban rail transit under network operation

Based on the framework of method of successive averages(MSA), a modified stochastic user-equilibrium assignment algorithm was proposed, which can be used to calculate the passenger flow distribution of urban rail transit(URT) under network operation. In order to describe the congestion's impact to passengers' route choices, a generalized cost function with in-vehicle congestion was set up. Building on the k-th shortest path algorithm, a method for generating choice set with time constraint was embedded, considering the characteristics of network operation. A simple but efficient route choice model, which was derived from travel surveys for URT passengers in China, was introduced to perform the stochastic network loading at each iteration in the algorithm. Initial tests on the URT network in Shanghai City show that the methodology, with rational calculation time, promises to compute more precisely the passenger flow distribution of URT under network operation, compared with those practical algorithms used in today's China.

AN ITERATION ALGORITHM FOR SOLVING POSTBUCKLING EQUILIBRIUM PATH OF SIMPLY-SUPPORTED RECTANGULAR PLATES UNDER BIAXIAL COMPRESSION

In this paper, on the basis of von Karman large deflection equations and its double trigonometric series solution, we present a simple, fast and effective iteration algorithm for solving simply-supported rectangular plate subjected to biaxial compression.

Calculation of Extraction Equilibrium in Multi-Component System by Newton-Raphson Algorithm

Based on the extraction equilibrium and mass balances in countercurrent extraction systems, a novel method was studied for dealing with the extraction equilibrium and the mass distribution in a multi-component(gamma-component) system. The relationships of mass distribution (x(i), y(i), i = 1, ..., lambda) between two phases were expressed by 2 lambda dimensional simultaneous equations. These simultaneous equations can be converted to a one-dimension nonlinear equation, then it was solved by Newton-Raphson algorithm within a few number of iteration. Compared with the regular calculation method for the 2 lambda dimensional simultaneous equations, Newton-Raphson algorithm can decrease the number of iteration, increase the convergence of the equations and accelerate the speed of simulation. It was verified in many multi-component systems with satisfactory results. As an example, a five-component system is demonstrated in this paper.

Convergence Theorem of Hybrid Iterative Algorithm for Equilibrium Problems and Fixed Point Problems of Finite Families of Uniformly Asymptotically Nonexpansive Semigroups

Throughout this paper, we introduce a new hybrid iterative algorithm for finding a common element of the set of common fixed points of a finite family of uniformly asymptotically nonexpansive semigroups and the set of solutions of an equilibrium problem in the framework of Hilbert spaces. We then prove the strong convergence theorem with respect to the proposed iterative algorithm. Our results in this paper extend and improve some recent known results.

ALGORITHMS FOR A SYSTEM OF GENERALIZED MIXED EQUILIBRIUM PROBLEMS AND A COUNTABLE FAMILY OF SOME NONLINEAR MULTI-VALUED NONEXPANSIVE-TYPE MAPS

In this paper, relaxed iterative algorithms of Krasnoselskii-type and Halpern-type that approximate a solution of a system of a generalized mixed equilibrium problem anda common fixed point of a countable family of totally quasi-C-asymptotically nonexpansivemulti-valued maps are constructed. Strong convergence of the sequence generated by thesealgorithms is proved in uniformly smooth and strictly convex real Banach spaces with Kadec-Klee property. Furthermore, several applications of our theorems are also presented. Finally,our theorems are significant improvements on several important recent results for this classof nonlinear problems.

Existence and algorithm of solutions for a system of generalized mixed implicit equilibrium problems in Banach spaces

A new system of generalized mixed implicit equilibrium problems is introduced and studied in Banach spaces. First, the notion of the Yosida proximal mapping for generalized mixed implicit equilibrium problems is introduced. By using the notion, a system of generalized equation problems is considered, and its equivalence with the system of generalized mixed implicit equilibrium problems is also proved. Next, by applying the system of generalized equation problems, we suggest and analyze an iterative algorithm to compute the approximate solutions of the system of generalized mixed implicit equilibrium problems. The strong convergence of the iterative sequences generated by the algorithm is proved under quite mild conditions. The results are new and unify and generalize some recent results in this field.

山区铁路桥隧工程关键节材要素均衡优化

为在经济可承受范围内提升山区铁路的节材性能,提出了一种基于NSGA-Ⅱ的关键节材要素双目标均衡优化方法。首先,以断面超挖、喷射混凝土类型选择、围岩变形预留、桩基扩孔、桩头超封5个桥隧工程关键节材要素为决策变量,以CO_(2)减排量最大、建造成本增加值最小为优化目标,构建山区铁路桥隧工程关键节材要素均衡优化模型;其次,采用带精英策略的非支配排序遗传算法(NSGA-Ⅱ)求出Pareto均衡解集;再次,耦合主客观元素组合的综合赋权法与TOPSIS法对Pareto均衡解集进行科学决策,得到考虑决策者偏好的关键节材要素最佳组合,并分析决策者偏好对最佳组合的影响;最后,以某山区铁路工程某标段为例,系统地验证了该方法的科学性及适用性。研究结果表明:与优化前相比,最佳组合能实现CO_(2)减排12.622万t,对应建造成本增加了24.833万元,优化效率达到50.826%。

PREDICTOR-CORRECTOR ALGORITHMS FOR SOLVING GENERALIZED MIXED IMPLICIT QUASI-EQUILIBRIUM PROBLEMS

A new class of generalized mixed implicit quasi-equilibrium problems （GMIQEP） with four-functions is introduced and studied. The new class of equilibrium problems includes many known generalized equilibrium problems and generalized mixed implicit quasi-variational inequality problems as many special cases. By employing the auxiliary principle technique, some predictor-corrector iterative algorithms for solving the GMIQEP are suggested and analyzed. The convergence of the suggested algorithm only requires the continuity and the partially relaxed implicit strong monotonicity of the mappings

基于混合平衡优化算法的疫苗配送路径优化

针对疫苗配送路径优化问题,在同时考虑固定成本、运输成本、制冷成本、碳排放成本和惩罚成本的情况下,提出以疫苗配送成本最小化为目标的车辆路径优化模型。为求解模型,在平衡优化器算法中引入模拟退火算法,改进平衡优化器算法容易陷入局部最优的不足,通过加入可变参数,提升算法平衡全局搜索和局部寻优的能力,得到一个能够稳定求出较高质量解的混合平衡优化算法。对2种不同规模的算例分别进行20次实验,将混合平衡优化算法与并行平衡优化算法、知识型蚁群算法、混合变邻域搜索算法、改进混合粒子群算法和平衡优化器算法进行对比。实验结果表明,混合平衡优化算法在小规模算例和大规模算例下得到的最小配送成本和配送成本的标准差都小于其他5种算法,其中,在小规模算例下进行实验后得到的最小配送成本分别为其他5种算法的73.5%、53.9%、69.1%、64.1%和33.4%。

基于改进平衡优化算法的折叠翼飞行器自抗扰控制器设计

针对折叠翼飞行器(FWV)模型误差和抗扰动能力较差及自抗扰控制器(ADRC)人工参数整定难的问题,提出一种基于莱维飞行的改进平衡优化(LEO)算法。给出典型FWV动力学模型,基于ADRC结构设计一种FWV的姿态控制器;在此基础上用所提算法整定了ADRC参数,并从控制性能和抗干扰的角度对经参数优化后的ADRC和传统ADRC进行仿真对比;将所提算法与经典平衡优化算法、粒子群优化(PSO)算法等进行仿真对比。仿真结果表明:所提算法优化的控制器能提高FWV的控制精度和扰动抑制性能,验证了所提算法在解决ADRC参数优化问题时的优越性。对搭载优化后ADRC的样机进行实飞验证,结果表明:在风扰之下,FWV样机仍具有较好的飞行性能指标,进一步验证了所提算法优化的ADRC对FWV抗扰能力的提升。

基于FCM和EO-SVM水轮机尾水管压力脉动特征识别

为有效识别水轮机尾水管压力脉动特征,提出了一种基于模糊C均值聚类、平衡优化器算法与支持向量机的识别方法。该方法首先采用平衡优化器算法优化SVM的惩罚因子和核函数以获得更好的SVM参数组合,构建EO-SVM识别模型以实现其在水轮机尾水管压力脉动特征识别中的应用。然后采用模糊C均值聚类算法将待分类的压力脉动特征进行初始聚类,将其分为四类,并依据聚类结果选择最靠近每类中心的样本作为EO-SVM模型的训练样本。将SVM和EO-SVM两种模型的识别分类结果进行比较,验证了所提EO-SVM模型的有效性。

基于改进黏菌算法的特征选择方法

[目的]在经常处理高维数据集的大数据时代中,特征选择是至关重要的.黏菌算法(slime mould algorithm,SMA)因其简单高效而被广泛应用于特征选择领域,并得到改进.然而,现有改进大多局限于策略添加和算法混合,未根据特征选择问题的特点进行深入改进.为此,本文提出了一种基于改进SMA(improved SMA,ISMA)的特征选择方法.[方法]首先,针对在特征选择时适应度函数值域较小导致的SMA全局探索和局部开发能力不平衡的问题,修改决定黏菌位置更新方式的参数;其次,针对SMA倾向往原点方向收敛的问题,改进SMA的位置更新公式;最后,针对SMA容易陷入局部最优的问题,提出一种基于均衡池改进黏菌位置更新公式的方法.进一步选取Musk1数据集和Lymphography数据集对比ISMA和SMA的全局探索和局部开发能力,并选取11个UCI数据集评价ISMA的性能.[结果]与SMA相比,ISMA具有更强的全局探索能力和局部开发能力,能够很好地平衡探索与开发.与SMA、GA和BGWO1等8种算法相比,ISMA在提高模型分类性能和降低特征维度上均有一定的竞争力.从平均分类准确率的角度看,与SMA相比,ISMA在所有数据集上均优于SMA,平均分类准确率最高提升6.53个百分点.与其他对比算法相比,ISMA在9个数据集上取得最优的平均分类准确率,而在剩下的2个数据集上也取得了次优的平均分类准确率,与第一名仅分别相差0.19个百分点和0.05个百分点,同时其平均维度缩减率均优于第一名.从平均维度缩减率的角度看,ISMA在2个数据集上取得最优的维度缩减率,总体表现良好.[结论]本文提出的基于ISMA的特征选择方法具有更高的泛化性能,与其他元启发式特征选择算法相比也有一定的优势.

利用建筑虚拟储能提升风电消纳能力的电热联合系统优化调度方法

利用建筑虚拟储能能提升电热联合系统的风电消纳能力,但若只考虑建筑结构储能而不考虑室内空气储能会导致虚拟储能利用不足。针对此问题,在奖惩阶梯碳交易背景下提出一种利用建筑虚拟储能提升风电消纳能力的电热联合系统优化调度方法。首先,以室内空气和建筑结构热平衡模型为基础建立精细化建筑虚拟储能模型;其次,在系统中引入奖惩阶梯碳交易机制及需求响应机制;再次,考虑电、热功率平衡以及室内温度等约束,以电热联合系统总成本最低为目标函数,并提出改进型平衡器优化算法对目标函数进行优化求解;最后,对不同场景下电热联合系统对风电的消纳、CO_(2)排放及经济性进行分析,结果表明:所提方法不仅提高了电热联合系统的风电消纳率,降低了CO_(2)的排放量,且提升了经济性。

基于子博弈完美均衡的启发式聚类算法

聚类是一种典型且重要的数据挖掘方法,但现有聚类算法大多需要人为指定聚类的数量,并且聚类结果对参数敏感.针对上述不足,本文提出一种基于子博弈完美均衡的启发式聚类算法(Heuristic Clustering algorithm based on Sub-game Perfect Equilibrium,HCSPE).该算法充分挖掘数据点自身的分布特征信息,通过启发式方法得到自适应的参数值,从而使数据点局部密度属性值的得出具有客观性和普适性,降低了聚类结果对参数的敏感性.基于博弈的思想,综合局部密度和相对距离两个属性形成数据点的竞争力,依靠竞争机制完成聚类数量的自动计算以及聚类中心的确定.在多个规模和类型均不相同的数据集上的实验结果表明,本文所提出算法的性能指标整体优于其他算法,并且聚类结果更符合客观所需.

Iterative algorithm for solutions to new system of generalized mixed implicit equilibrium

A new system of generalized mixed implicit equilibrium problems （SGMIEP） involving nonmonotone set-valued mappings is introduced and studied in real reflexive Banach spaces. First, an auxiliary mixed equilibrium problem （AMEP） is introduced. The existence and the uniqueness of the solutions to the AMEP are proved under quite mild assumptions without any coercive conditions. Next, by using the solution mapping of the AMEP, a system of generalized equation problems （SGEP） is considered, and its equivalence with the SGMIEP is shown. By using the SGEP, a new iterative algorithm for solving the SGMIEP is proposed and analyzed. The strong convergence of the iterative sequences generated by the algorithm is proved under suitable conditions. These results are new, which unify and generalize some recent results in this field.

基于改进多目标平衡优化器算法的点焊机器人路径规划

点焊机器人在工业领域内被广泛应用,合理的焊接顺序可以提高生产效率。为了实现点焊机器人的路径最优规划,针对点焊路径和工作时间建立多目标问题模型,提出一种融合改进快速非支配排序的多目标平衡优化器算法(DMONEO)。加入快速非支配排序,并采用生存评分策略替代拥挤度因子,可以更好地保持种群的多样性,防止DMONEO过早收敛。TSPLIB基准实验结果表明,DMONEO算法相比于其他算法性能表现更好。最后在实际点焊机器人的路径规划应用中进行仿真实验并与其他算法对比,结果表明提出的算法得到的优化效果更好,耗时更短。

基于自适应交叉与协方差学习的改进平衡优化器算法

针对平衡优化器算法存在的收敛精度低和易陷入局部停滞的问题,提出一种基于自适应交叉与协方差学习的改进平衡优化器算法。首先,构建外部存档来保留历史优势个体,增加种群多样性,以提高算法的全局寻优能力。其次,引入自适应交叉概率来平衡算法的全局探索能力和局部开发能力,以提高算法的寻优精度和鲁棒性。最后,采用协方差学习策略,充分利用浓度向量之间的关系来增强种群间信息交流,以避免算法陷入局部停滞。通过对CEC2019测试函数进行仿真实验,并将改进算法与反向传播(back propagation,BP)神经网络相结合用于预测新疆玛纳斯河的径流情况,实验结果表明,改进算法在收敛精度和鲁棒性方面有显著提升,且大幅提高了BP神经网络的径流预测效果。