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1.
Simulated annealing type algorithms for multivariate optimization   总被引:1,自引:0,他引:1  
We study the convergence of a class of discrete-time continuous-state simulated annealing type algorithms for multivariate optimization. The general algorithm that we consider is of the formX k +1 =X k a k (U(X k ) + k) +b k W k . HereU(·) is a smooth function on a compact subset of d , {k} is a sequence of d -valued random variables, {W k } is a sequence of independent standardd-dimensional Gaussian random variables, and {a k }, {b k } are sequences of positive numbers which tend to zero. These algorithms arise by adding decreasing white Gaussian noise to gradient descent, random search, and stochastic approximation algorithms. We show under suitable conditions onU(·), { k }, {a k }, and {b k } thatX k converges in probability to the set of global minima ofU(·). A careful treatment of howX k is restricted to a compact set and its effect on convergence is given.Research supported by the Air Force Office of Scientific Research contract 89-0276B, and the Army Research Office contract DAAL03-86-K-0171 (Center for Intelligent Control Systems).  相似文献   

2.
模拟退火教学式优化算法   总被引:4,自引:0,他引:4  
针对教学式优化算法在求解组合优化问题时易陷入局部最优问题进行了研究,提出模拟退火教学式优化算法.利用模拟退火方法,在“教”与“学”两个阶段按照模拟退火计算的概率,随机接受个体中某一位较差解作为新解的一部分.通过增加群体多样性的方法,增强教学式优化算法逃离局部最优解的能力.分别对单模、多模和旋转函数进行仿真,并与其他算法进行了对比实验.结果表明,提出的方法在收敛速度和收敛精度上具有较好的性能.  相似文献   

3.
随机优化问题一类基于假设检验的模拟退火算法   总被引:5,自引:1,他引:5  
王凌  郑大钟 《控制与决策》2004,19(2):183-186
针对随机优化问题的不确定性,提出一类基于假设检验的模拟退火算法.该方法通过多次评价来合理估计解的性能,利用假设检验减少重复性搜索,采用突跳性搜索避免局部极小,并通过温度控制调节突跳能力.数值仿真研究了假设检验、性能估计、噪声幅度对算法性能的影响,其结果验证了该方法的有效性和鲁棒性.  相似文献   

4.
In this paper, three simulated annealing based algorithms that exploit auxiliary knowledge in different ways are devised and employed to handle a manufacturing process planning problem for reconfigurable manufacturing. These algorithms are configured based on a generic combination of the simulated annealing technique with; (a) heuristic knowledge, and (b) metaknowledge. Capabilities of the implemented algorithms are tested and their performances compared against a basic simulated annealing algorithm. Computational and optimization performances of the implemented algorithms are investigated and analyzed for two problem sizes. Each problem size consists of five different forms of a manufacturing process planning problem. The five forms are differentiated by five alternative objective functions. Experimental results show that the implemented simulated annealing algorithms are able to converge to good solutions in reasonable time. A computational analysis indicates that significant improvements towards a better optimal solution can be gained by implementing simulated annealing based algorithms that are supported by auxiliary knowledge.  相似文献   

5.
在进行MRI(magneticresonanceimaging)超导主磁体的设计时常采用优化设计的方法,将各设计参数看作连续变量处理,但实际上很多参数是离散变量,为了更符合工程实际,将超导MRI主磁体的设计作为一个含有离散变量的全局优化问题。建立了适用于多种超导MRI主磁体结构的数学模型,包括设计变量、目标函数、约束条件等,选用了适用于MRI超导主磁体优化设计的含有离散变量的模拟退火算法进行设计。算例结果表明,本文选取的数学模型和优化算法是有效的,能够达到超导MRI主磁体设计的要求。  相似文献   

6.
7.
Genomic data, and more generally biomedical data, are often characterized by high dimensionality. An input selection procedure can attain the two objectives of highlighting the relevant variables (genes) and possibly improving classification results. In this paper, we propose a wrapper approach to gene selection in classification of gene expression data using simulated annealing along with supervised classification. The proposed approach can perform global combinatorial searches through the space of all possible input subsets, can handle cases with numerical, categorical or mixed inputs, and is able to find (sub-)optimal subsets of inputs giving low classification errors. The method has been tested on publicly available bioinformatics data sets using support vector machines and on a mixed type data set using classification trees. We also propose some heuristics able to speed up the convergence. The experimental results highlight the ability of the method to select minimal sets of relevant features.  相似文献   

8.
In this article we present a simulated annealing based algorithm for the determination of optimal ship routes through the minimization of a cost function defined as a weighted sum of the time of voyage and the voyage comfort (safety is taken into account too). This cost function is dependent on the wind speed and its direction as well as on the wave height and its direction. The constructed algorithm at the beginning discretizes an initial route and then optimizes it by considering small deviations, which are accepted or rejected by utilizing the simulated annealing technique. Using calculus of variations, we prove a key theorem which tremendously accelerates the convergence of the proposed algorithm. For an illustration of the advantages of the constructed method, both computational and real experiments have been carried out which are presented and discussed.  相似文献   

9.
课程表问题是经典的组合优化问题,属于NP-hard问题.长期以来人们一直都在寻求快速高效的近似算法,以便在合理的计算时间内准确解决大规模课程安排问题,并提出许多有效且实用的启发式和元启发式算法.在此基础上提出了一种基于多个图染色启发式规则的模拟退火超启发式算法.在超启发式算法的框架中,用模拟退火算法作为高层搜索算法,多个图染色启发式规则为底层的构造算法.与现有的方法相比,该算法具有很好的通用性,可以很容易推广到考试时间表、会议安排.旅行商问题、背包问题等应用领域.实验表明,该算法是可行有效的,且无一例时间、空间冲突.  相似文献   

10.
Optimal utilization of resources in present-day communication networks is a challenging task. Routing plays an important role in achieving optimal resource utilization. The open shortest path first (OSPF) routing protocol is widely used for routing packets from a source node to a destination node. This protocol assigns weights (or costs) to the links of a network. These weights are used to determine the shortest path between all sources to all destination nodes. Assignment of these weights to the links is classified as an NP-hard problem. This paper formulates the OSPF weight setting problem as a multi-objective optimization problem, with maximum utilization, number of congested links, and number of unused links as the optimization objectives. Since the objectives are conflicting in nature, an efficient approach is needed to balance the trade-off between these objectives. Fuzzy logic has been shown to efficiently solve multi-objective optimization problems. A fuzzy cost function for the OSPF weight setting problem is developed in this paper based on the Unified And-OR (UAO) operator. Two iterative heuristics, namely, simulated annealing (SA) and simulated evolution (SimE) have been implemented to solve the multi-objective OSPF weight setting problem using a fuzzy cost function. Results are compared with that found using other cost functions proposed in the literature (Sqalli et al. in Network Operations and Management Symposium, NOMS, 2006). Results suggest that, overall, the fuzzy cost function performs better than existing cost functions, with respect to both SA and SimE. Furthermore, SimE shows superior performance compared to SA. In addition, a comparison of SimE with NSGA-II shows that, overall, SimE demonstrates slightly better performance in terms of quality of solutions.  相似文献   

11.
12.
提出了一种求解二次分配问题的模拟退火蚁群算法。将模拟退火机制引入蚁群算法,在算法中设定随迭代变化的温度,将蚁群根据信息素矩阵搜索得到的解集作为候选集,根据当前温度按照模拟退火机制由候选集生成更新集,利用更新集更新信息素矩阵,并利用当前最优解对信息素矩阵进行强化。当算法出现停滞对信息素矩阵进行重置。实验表明,该算法有着高的稳定性与收敛速度。  相似文献   

13.
Three new algorithms for multivariate polynomial GCD (greatest common divisor) are given. The first is to calculate a Gröbner basis with a certain term ordering. The second is to calculate the subresultant by treating the coefficients w.r.t. the main variable as truncated power series. The third is to calculate a PRS (polynomial remainder sequence) by treating the coefficients as truncated power series. The first algorithm is not important practically, but the second and third ones are efficient and seem to be useful practically. The third algorithm has been implemented naively and compared with the trial-division PRS algorithm and the EZGCD algorithm. Although it is too early to derive a definite conclusion, the PRS method with power series coefficients is very efficient for calculating low degree GCD of high degree non-sparse polynomials.  相似文献   

14.
A class of scientific images, which we will call blot images, contains information in the form of relationships between grey level pixels. One way to extract this information is to fit model functions to the objects in the image. We have explored the use of a Moffat function as a data model, and use the technique of simulated annealing to fit many instances of this function to the data in the image. Two examples are presented: stellar photometry, a natural application for the Moffat function, and reading DNA sequencing gels.This work has been supported by the National Sciences and Engineering Research Council of Canada.  相似文献   

15.
Immune-based algorithms for dynamic optimization   总被引:4,自引:0,他引:4  
The main problem with biologically inspired algorithms (like evolutionary algorithms or particle swarm optimization) when applied to dynamic optimization is to force their readiness for continuous search for new optima occurring in changing locations. Immune-based algorithm, being an instance of an algorithm that adapt by innovation seem to be a perfect candidate for continuous exploration of a search space. In this paper we describe various implementations of the immune principles and we compare these instantiations on complex environments.  相似文献   

16.
The Self-Organizing Map (SOM) is a popular unsupervised neural network able to provide effective clustering and data visualization for multidimensional input datasets. In this paper, we present an application of the simulated annealing procedure to the SOM learning algorithm with the aim to obtain a fast learning and better performances in terms of quantization error. The proposed learning algorithm is called Fast Learning Self-Organized Map, and it does not affect the easiness of the basic learning algorithm of the standard SOM. The proposed learning algorithm also improves the quality of resulting maps by providing better clustering quality and topology preservation of input multi-dimensional data. Several experiments are used to compare the proposed approach with the original algorithm and some of its modification and speed-up techniques.  相似文献   

17.
针对网格开放性和扩展性的需求,提出了基于Overlay Network网格体系结构的理论模型。形式化了其核心问题:混合Overlay Network拓扑设计问题,证明了该问题在满足一定条件下具有线性复杂度,提出了在一般条件下求解该问题的模拟退火算法。最后,通过仿真实验分析评价了所提出算法对Overlay Network拓扑代价的影响,结果表明这个模拟退火算法是可行的。  相似文献   

18.
In today's economy, manufacturing plants must be able to operate efficiently and respond quickly to changes in product mix and demand. Therefore, this paper considers the problem of arranging and rearranging (when there are changes between the flows of materials between departments) manufacturing facilities such that the sum of the material handling and rearrangement costs is minimized. This problem is known as the dynamic facility layout problem (DFLP). In this paper, two simulated annealing (SA) heuristics are developed for the DFLP. The first SA heuristic (SA I) is a direct adaptation of SA to the DFLP. The second SA heuristic (SA II) is the same as SA I with a look-ahead/look-back strategy added. To test the performance of the heuristics, a data set taken from the literature is used in the analysis. The results obtained show that the proposed heuristics are very effective for the dynamic facility layout problem.  相似文献   

19.
结合Metropolis准则,对模拟退火算法进行了研究.阐述了模拟退火算法的基本原理及其实现过程,在Visual C 编译环境下实现了该算法.并将其运用到解决旅行商问题的优化之中.介绍了TSP的问题特征、一般形式及其数学描述,确定了其VC 环境下的模型实现步骤.实例仿真的结果表明了该方法能够对函数进行全局寻优,有效克服了基于导数的优化算法容易陷入局部最优的问题.该方法既可以增加对C 语言的掌握又可以加深对模拟退火过程的认识,并达到以此来设计智能系统的目的.  相似文献   

20.
Li  Zewen  Zhang  Qisheng  He  Yichao 《Applied Intelligence》2022,52(10):11300-11323
Applied Intelligence - Group Theory-based Optimization Algorithm (GTOA) is a novel population-based global optimization algorithm, which is used to solve combinatorial optimization problems. This...  相似文献   

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