求解全局优化问题的改进蝙蝠算法[英文]

蝙蝠算法(BA)是一类基于试探技巧的群智能优化算法,该算法已被广泛用于诸多领域问题的求解.本文提出一个改进的蝙蝠算法NIBA.在算法中,为了加强蝙蝠算法的局部和全局搜索能力,提出了三个改进策略.首先,为了改进蝙蝠的局部搜索能力,在当前最优解处给出了一个新的搜索方程.其次,为了改进算法的全局搜索能力,平衡算法的开发能力和探索能力,算法吸收并改进了和声搜索机制.最后,为了进一步提高NIBA算法的搜索能力,在当前最优解处,算法采用了混沌搜索机制.为了验证算法的性能,针对18个标准测试函数进行了数值实验.与其它算法的比较结果显示,NIBA算法具有更好的稳定性,且效率更高.     

比例风险模型下参数极大似然估计的自适应优化算法及其改进算法

自适应优化算法可避免很多常用数值算法遭遇的困难,例如:高维矩阵求逆问题,初值选取的问题和算法的收敛问题等等.因此,自适应优化算法得到了迅速的发展和广泛的应用,本文研究了比例风险模型下的自适应优化算法.首先利用三种自适应优化算法-Adam算法、RMSprop算法、Adagrad算法求解比例风险模型下的参数估计数值解问题,获得了自适应算法的计算优良性.然后,推广了比例风险模型下的Adam算法的研究,发展了一种改进的Adam算法,进一步提高了算法的计算速度并展现了其计算优势.     

求解Sylvester矩阵方程的一种改进的梯度方法

提出了一种改进的梯度迭代算法来求解Sylvester矩阵方程和Lyapunov矩阵方程.该梯度算法是通过构造一种特殊的矩阵分裂,综合利用Jaucobi迭代算法和梯度迭代算法的求解思路.与已知的梯度算法相比,提高了算法的迭代效率.同时研究了该算法在满足初始条件下的收敛性.数值算例验证了该算法的有效性.     

矩阵填充的硬阈值修正算法

提出了使用硬阈值进行矩阵填充的修正算法.算法通过对迭代矩阵进行对角修正来完成矩阵填充,并给出了算法的收敛性分析.最后通过数值实验比较了修正算法与硬阈值算法填充的数值结果,显示出了新算法的优越性.     

偏微分方程的局部保结构算法

讨论偏微分方程的局部保结构算法,它是原来的整体保结构算法的自然推广. 当边界条件适宜时, 局部保结构算法自然是整体保结构算法, 但整体保结构算法却不一定是局部保结构算法. 局部保结构算法的概念能解释不同保结构算法之间的差异性, 也能为分析和构造性能较好的保结构算法提供理论基础. 不仅如此, 合适的边界条件不再是局部保结构算法可应用于偏微分方程的必要条件, 从而拓宽了保结构算法的适用性. 还讨论了局部保结构算法的应用和系统构造问题, 得到了非线性Klein-Gordon方程的一些新的格式.     

非线性互补问题的两种数值解法

本文研究了非线性互补问题的两类数值求解方法.在经典LQP算法及LevenbergMarquardt算法的基础上,构造了两种新算法,并证明了这两种新算法的收敛性.数值实验表明,新算法对测试问题优于已有算法.     

学习算法的稳定性与泛化(Ⅱ):有界差分稳定框架

根据有界差分条件,提出了学习算法的有界差分稳定框架.依据新框架,研究了机器学习阈值选择算法,再生核Hilbert空间中的正则化学习算法,Ranking学习算法和Bagging算法,证明了对应学习算法的有界差分稳定性.所获结果断言了这些算法均具有有界差分稳定性,从而为这些算法的应用奠定了理论基础.     

一类凸二次规划的新算法

本文给出了求解一类凸二次规划问题的新算法.这种算法既保留了传统算法的优点,又避免了其它算法中出现的添加人工变量过多、循环等问题.算例表明,这种算法是简便而有效的.     

凸可行问题的一种强收敛算法

无限维Hilbert空间中,解凸可行问题的平行投影算法通常是弱收敛的.本文对一般的平行投影算法进行改进,设计了一种解凸可行问题的具有强收敛性的新算法.该算法主要是在原有算法基础上引入了一个参数序列,在参数序列满足一定的控制条件下保证了算法的强收敛性.为了简单证明算法的强收敛性,我们构建了一个新的积空间,然后把原空间的这种改进平行投影算法转换为积空间中的交替投影算法.这样,改进的平行投影算法的强收敛性就可以通过交替投影算法的收敛性证明得到.     

一类凸优化的加速混合下降算法

凸优化问题的混合下降算法利用近似条件的已知信息和随机数扩张预测校正步得到了一组下降方向.而前向加速收缩算法利用高斯赛德尔迭代算法的技术,结合邻近点算法和近似邻近点算法的思想,构造了富有扩张性的下降方向.本文借鉴混合下降算法和前向加速收缩算法的思想,利用已有近似规则信息改善了混合下降算法的下降方向,得到了一类凸优化问题的加速混合下降算法.随后利用Markov不等式、凸函数性质和投影的基本性质等,实现了算法的依概率收敛证明.一系列数值试验表明了加速混合下降算法的有效性和效率性.     

一类关于非光滑全局优化的双参数填充函数

为在有界闭集上寻找非光滑函数的全局极小点,本文在文献[12]的基础上提出了一个改进的填充函数定义,然后给出了一个新的双参数填充函数.讨论了所给填充函数的理论和数值性质并设计了相应的算法.分析表明所给填充函数对参数的选择优于相关文献中的结果.数值实验表明,本文所给出的新的填充函数算法是有效的.     

基于PSO-MAs算法的产品组合问题研究

针对多约束的产品组合问题,提出一种基于PSO的Memetic算法。该算法首先运用约束理论识别并剔除非瓶颈约束,然后基于伪效用比率设计了一个局部搜索算法,并将其加入到PSO算法的种群进化中,以增强PSO算法的局部学习能力。通过对算法在小规模和大规模算例中测试,表明该算法在小规模问题中优于许多已有算法,同时能在相对较短地时间内更有效地求解较大规模产品组合问题。因此本文提出的基于PSO的Memetic算法可以用来有效地求解实际中的产品组合问题。     

Two new conjugate gradient methods based on modified secant equations

Following the approach proposed by Dai and Liao, we introduce two nonlinear conjugate gradient methods for unconstrained optimization problems. One of our proposed methods is based on a modified version of the secant equation proposed by Zhang, Deng and Chen, and Zhang and Xu, and the other is based on the modified BFGS update proposed by Yuan. An interesting feature of our methods is their account of both the gradient and function values. Under proper conditions, we show that one of the proposed methods is globally convergent for general functions and that the other is globally convergent for uniformly convex functions. To enhance the performance of the line search procedure, we also propose a new approach for computing the initial steplength to be used for initiating the procedure. We provide a comparison of implementations of our methods with the efficient conjugate gradient methods proposed by Dai and Liao, and Hestenes and Stiefel. Numerical test results show the efficiency of our proposed methods.     

A novel of fuzzy PSS based on new objective function in multimachine power system

This article proposed a new control strategy based on Takagi–Sugeno fuzzy model for deceasing the power system oscillation. This controller is based on the parallel distributed compensation structure, the stability of the whole closed‐loop model is provided using a general Lyapunov‐Krasovski functional. Also, in this article, a new objective function has been considered to test the proposed Fuzzy Power System Stabilizer in different load conditions which increase the system damping after the system undergoes a disturbance. So, for testing the effectiveness of the proposed controller, the damping factor, damping ratio, and a combination of the damping factor and damping ratio were analyzed and compared with the proposed objective function. The effectiveness of the proposed strategy has been used over 16 machine 68 bus power system. The eigenvalue analysis and nonlinear time domain simulation results proof the effectiveness of the proposed method. © 2015 Wiley Periodicals, Inc. Complexity 21: 288–298, 2016     

The Extended Alpha-triple I Algorithm Based on the Generalized Implication Operator

In this paper, the classical implication operator is generalized, and then the definition of generalized implication operator on [0, 1] is proposed. Based on generalized implication operator, the extended alpha-triple I principle is presented by generalizing the alpha-triple I algorithm. By analyzing the essence of alpha-triple Fuzzy Modus Ponens (FMP) and alpha-triple Fuzzy Modus Tollens (FMT) principles, and based on the generalized implication operator, the generalized calculating formula of extended alpha-triple I algorithm is proposed. At the same time, the reversibility on the proposed alpha-triple I algorithm is discussed. It is proved that Compositional Rule of Inference (CRI) is a special case of extended alpha-triple I algorithm. Finally, two implication operations are proposed to validate the proposed generalized equation.     

A dynamic multi-objective optimization model with interactivity and uncertainty for real-time reservoir flood control operation

Despite the successes of both multi-objective optimization and uncertainty handling techniques in reservoir flood control operation, no work has been done yet on developing and investigating dynamic multi-objective optimization models for this problem. In this work, a dynamic multi-objective optimization model with interactivity and uncertainty was developed for the real-time reservoir flood control operation. Accordingly, a dynamic multi-objective optimization algorithmic framework with two newly designed change reaction strategies was proposed for solving the proposed dynamic model. Following the proposed algorithmic framework, any evolutionary multi-objective optimization algorithm can be converted into a dynamic optimizer. After investigating the difficulty variation of the proposed dynamic model, the effectiveness and robustness of the proposed algorithmic framework have been validated based on experiential studies on two typical floods of Ankang reservoir.     

A Model for Evaluation of Transport Policies in Multimodal Networks with Road and Parking Capacity Constraints

This paper presents a model for evaluation of transport policies in multimodal networks with road and parking capacity constraints. The proposed model simultaneously considers choices of travelers on route, parking location and mode between auto and transit. In the proposed model, it is assumed that auto drivers make a simultaneous route and parking location choice in a user equilibrium manner, and the modal split between auto and transit follows a multinomial logit formulation. A mathematical programming model with capacity constraints on road link and parking facilities is proposed that generates optimality conditions equivalent to the requirements for multimodal network equilibrium. An augmented Lagrangian dual algorithm embedded by partial linearization approach is developed to solve the proposed model. Numerical results on two example networks are presented to illustrate the proposed methodology. The results show that the service level of transit, parking charges, road link and parking capacities, and addition of a new parking location may bring significant impacts on travelers’ behavior and network performance. In addition, transport policies may result in paradoxical phenomenon.     

求解带组换装时间单机调度问题的禁忌搜索算法

以包头某钢铁线材企业生产实际调度问题为背景,研究了一类带组换装时间的单机调度问题.由于该问题是NP难的,本文提出了一类适合该问题的禁忌搜索算法.此外,本文将问题性质引入了禁忌搜索算法以进一步提高算法寻优性能,降低算法运行时间.本文提出的算法在随机问题和实际问题上均进行了测试,实验结果表明,本文提出的算法能在不到10秒的时间内获得实际问题的一个近似最优解.     

Testing quasi-independence for truncation data

Quasi-independence is a common assumption for analyzing truncated data. To verify this condition, we propose a class of weighted log-rank type statistics that include existing tests proposed by Tsai (1990) and Martin and Betensky (2005) as special cases. To choose an appropriate weight function that may lead to a more power test, we derive a score test when the dependence structure under the alternative hypothesis is modeled via the odds ratio function proposed by Chaieb, Rivest and Abdous (2006). Asymptotic properties of the proposed tests are established based on the functional delta method which can handle more general situations than results based on rank-statistics or U-statistics. Extension of the proposed methodology under two different censoring settings is also discussed. Simulations are performed to examine finite-sample performances of the proposed method and its competitors. Two datasets are analyzed for illustrative purposes.     

Sequencing by hybridization: an enhanced crossover operator for a hybrid genetic algorithm

This paper presents a genetic algorithm for an important computational biology problem. The problem appears in the computational part of a new proposal for DNA sequencing denominated sequencing by hybridization. The general usage of this method for real sequencing purposes depends mainly on the development of good algorithmic procedures for solving its computational phase. The proposed genetic algorithm is a modified version of a previously proposed hybrid genetic algorithm for the same problem. It is compared with two well suited meta-heuristic approaches reported in the literature: the hybrid genetic algorithm, which is the origin of our proposed variant, and a tabu-scatter search algorithm. Experimental results carried out on real DNA data show the advantages of using the proposed algorithm. Furthermore, statistical tests confirm the superiority of the proposed variant over the state-of-the-art heuristics.