一种基于禁忌搜索的全局最优化模糊聚类算法

模糊C均值（FCM）算法是一种基于贪心思想的迭代算法,算法沿迭代序列收敛到一个极小值,但存在搜索能力弱、易陷入局部最优的缺点.本文提出了一种基于禁忌搜索的模糊聚类算法,该算法在一个解的邻域内使用禁忌搜索,并采用了基于FCM局部收敛性质的长期表禁忌策略,保证在不断移动搜索起点的同时避免重复搜索;其次使用混沌优化思想与动态步长策略来提升算法的全局搜索能力,以达到获取全局最优解的目的.实验结果表明,改进算法极大地提高了聚类准确率,并具有良好的稳定性,与群智算法和遗传算法的优化相比也具有一定的优势.     

一种基于禁忌搜索的多用户检测方法

本文提出一种实现码分多址(ＣＤＭＡ)系统上多用户检测(ＭＵＤ)的禁忌搜索(ｔａｂｕｓｅａｒｃｈ)的方法。 该方法利用传统检测方法的输出作为初始解,直接应用禁忌搜索算法来解决最佳多用户检测的非线性优化组合问题。通过分析以及对同步和异步情况的仿真表明,该方法简单易于实现,具有多项式的计算复杂度,对远近问题不敏感,并且能够得到与最佳检测方法(ＯＤ)非常接近的误码率性能和抗多址干扰性能．     

量子禁忌搜索算法的研究

针对量子智能算法对高维函数的优化时存在容易陷入局部最优的问题,提出了量子禁忌搜索算法.在量子比特相位增量空间方面,提出了一种按指数级别下降并可动态循环调整的策略;在候选解相位邻域空间方面,提出了一种与禁忌表中最优解有关的可动态调整的划分方法,并增加了候选解局部优化处理方法.为了验证算法的有效性,在高维函数极值问题和多维背包问题进行了仿真,结果表明本文算法收敛速度快,求解精度高.     

粗神经网络的禁止搜索训练算法研究

粗神经网络不仅可以处理明确定量的输入信息,而且可以处理传统神经网络不能处理的语义形式的输入信息.本文给出了一种新的训练方法--基于禁止搜索算法的粗神经网络训练方法.仿真结果表明本文提出的训练算法在收敛速度和网络性能上都有显著提高.     

禁忌搜索算法在系统可靠性分配中的应用

关于可靠性分配的研究已取得了一定的进展,但对于复杂系统的可靠性分配问题,应用传统的方法,很难准确、科学地进行可靠性分配。鉴于此情况,提出应用禁忌搜索算法对复杂系统的可靠性进行分配,以便科学、合理地分配系统可靠性。首先简要介绍了禁忌搜索算法的概念、思想及求解过程,并结合可靠性分配问题,验证了算法在可靠性分配中的应用。     

引入逆学习的量子自适应禁忌搜索算法

为增强量子进化算法的局部优化能力,结合禁忌搜索思想,提出一种具有逆学习机制的量子自适应禁忌搜索算法.算法采用一种量子自适应邻域映射机制,且禁忌表的禁忌长度可随量子态动态调整,这些策略较好的解决了集中性和多样性搜索的矛盾.另外,算法增加了一种能使个体尽快摆脱劣势区域的逆学习量子更新模式.设计的算法能较好的平衡全局和局部搜索,能有效避免量子过快陷入局部极值.通过实验表明提出的算法具有更好的局部搜索能力.     

Channel Assinment Using Tabu Search in Wireless Mesh Networks

Wireless Personal Communications - Wireless networks pave a way for faster and quicker transmission. The most important terminology in mesh networking is assigning proper channel for faster...     

求解二次分配问题的改进禁忌搜索算法

针对二次分配问题,提出了一种改进禁忌搜索算法ITS。ITS基于"集中和分散"策略,由局部搜索和精英重组两个步骤经过多次迭代完成。局部搜索采用RTS(Robust Tabu Search)。在精英重组步骤,对局部优化解中的优良个体采用MPX交叉操作,得到新的可行解。在QAPLIB典型实例上的实验结果表明,与RTS相比,改进后的禁忌搜索算法具有更优的性能。     

变邻域结构Tabu搜索算法及其在JobShop调度问题上的应用

本文针对最小化完工时间的Job Shop调度问题提出一种变邻域结构Tabu搜索算法,该算法使用的邻域结构随算法的进程而改变,不仅邻域规模小,而且仍保持了可达性这一重要的属性.对不同规模的实例进行了数值计算,计算结果表明,该算法具有非常高的效率,且初始解对算法的影响很小.     

Routing Protocol Based on Tabu Search for Wireless Sensor Networks

This paper investigates the proposition of a new routing protocol for wireless sensor networks called TSRP (Tabu Search based Routing Protocol). In this protocol, we use the mechanism of the meta-heuristic Tabu search to route the data from the sensor (that has sense the events) to the sink. This mechanism is used to select the next sensor that will route the data based on a cost function (considering the energy and the visibility of this sensor compared to the sink). Simulation results, on a car parking application, show that TSRP prolongs the network lifetime than the existing protocols.     

基于改进禁止搜索算法的矢量量化码书设计

本文提出了基于改进禁止搜索(TS)算法的矢量量化(VQ)码书设计方法.禁止搜索算法的关键是如何定义一个解以及如何在当前解的基础上生成邻域解.由于码书设计的两个优化准则是最邻近条件和聚类质心条件,本文提出了两种禁止搜索算法的解描述方案,其相应算法分别叫基于码书的禁止搜索(CB-TS)算法和基于聚类划分的禁止搜索(PB-TS)算法.为了提高禁止搜索算法的性能,文中在禁止搜索算法中融入了模拟退火(SA)机制.为了进一步提高码书性能,文中还将码书设计的传统LBG算法融入禁止搜索算法中.结果表明,基于禁止搜索的两种码书设计方案所生成的码书性能都比LBG算法有明显提高.     

Cloud Dynamic Scheduling for Multimedia Data Encryption Using Tabu Search Algorithm

The cloud computing is interlinked with recent and out-dated technology. The cloud data storage industry is earning billion and millions of money through this technology. The cloud remote server storage is on-demand technology. The cloud users are expecting higher quality in minimal cost. The quality of service is playing a vital role in any latest technology. The cloud user always depends on thirty party service providers. This service provider is facing higher competition. The customer is choosing a service based on two parameters one is security and another one is cost. The reason behind this is all our personal data is stored on some third party server. The customer is expecting higher security level. The service provider is choosing many techniques for data security, best one is encryption mechanism. This encryption method is having many algorithms. Then again one problem is raised, that is which algorithm is best for encryption. The prediction of algorithm is one of major task. Each and every algorithm is having unique advantage. The algorithm performance is varying depends on file type. The proposed method of this article is to solve this encryption algorithm selection problem by using tabu search concept. The proposed method is to ensure best encryption method to reducing the average encode and decode time in multimedia data. The local search scheduling concept is to schedule the encryption algorithm and store that data in local memory table. The quality of service is improved by using proposed scheduling technique.

     

A Tabu Search Algorithm for Cluster Building in Wireless Sensor Networks

The main challenge in wireless sensor network deployment pertains to optimizing energy consumption when collecting data from sensor nodes. This paper proposes a new centralized clustering method for a data collection mechanism in wireless sensor networks, which is based on network energy maps and Quality-of-Service (QoS) requirements. The clustering problem is modeled as a hypergraph partitioning and its resolution is based on a tabu search heuristic. Our approach defines moves using largest size cliques in a feasibility cluster graph. Compared to other methods (CPLEX-based method, distributed method, simulated annealing-based method), the results show that our tabu search-based approach returns high-quality solutions in terms of cluster cost and execution time. As a result, this approach is suitable for handling network extensibility in a satisfactory manner.     

Assigning cells to switches in cellular mobile networks using hybridizing API algorithm and Tabu Search

Cells assignment to switches plays an important role in the area of resource management in cellular network. Efficient homing of cells to switches can have a significant impact on handoff and cabling costs. This problem is an NP‐hard problem, which cannot be solved by conventional optimization algorithms. It is therefore necessary to use metaheuristic methods to solve it. This research proposes a hybrid heuristic approach for further improving the quality of solutions. This approach applies API ant algorithm in combination with one of the best heuristics used to solve this problem: Tabu Search. A key element in the success of this hybrid approach is the use simultaneously an intensified research on several areas of research space. The implementation of these algorithms has been subject to extensive tests. In comparison with previous research, the proposed method is efficient, regarding quality of solutions provided for moderate‐sized and large‐sized cellular mobile networks. Copyright © 2013 John Wiley & Sons, Ltd.     

基于PRI熵的雷达信号聚类方法研究

针对脉冲分选聚类中存在的问题,引入熵的概念,定义了 PRI(脉冲重复间隔)熵,给出了雷达脉冲序列之间合并的 PRI 熵判据.并在此基础上提出了新的雷达信号聚类方法.采用先分选后合并的思路,通过计算合并前后 PRI 熵是否减小来判断是否对序列合并.通过仿真验证该方法解决增批问题的有效性.     

Hopfield Neural Network Approach to Clustering in Mobile Radio Networks

ＨｏｐｆｉｅｌｄＮｅｕｒａｌＮｅｔｗｏｒｋＡｐｐｒｏａｃｈｔｏＣｌｕｓｔｅｒｉｎｇｉｎＭｏｂｉｌｅＲａｄｉｏＮｅｔｗｏｒｋｓＪｉａｎｇＹａｎ；ＬｉＣｈｅｎｇｓｈｕ（ＮｏｒｔｈｅｒｎＪｉａｏｔｏｎｇＵｎｉｖｅｒｓｉｔｙ，Ｂｅｉｊｉｎｇ１０００４４）Ａｂ...     

基于函数复杂度的自适应模拟退火和禁忌搜索新算法

在求解多峰复杂函数的过程中,传统的模拟退火算法和禁忌搜索算法经常出现算法快速收敛于局部最优解、后期收敛速度变慢和搜索能力变差等问题.为解决这些问题,本文给出函数复杂度的定义,并提出基于函数复杂度的自适应模拟退火和禁忌搜索算法.该算法首先根据函数复杂度自适应调整步长控制参数,然后根据调整后步长求得函数的粗糙解,在此基础上再使用初始步长求得全局最优解.实验表明,该算法不仅可以跳出局部最优解的限制,并且减少了迭代次数,有效地提高了全局和局部搜索能力.     

System Level Hardware/Software Partitioning Based on Simulated Annealing and Tabu Search

This paper presents two heuristics for automatic hardware/software partitioning of system level specifications. Partitioning is performed at the granularity of blocks, loops, subprograms, and processes with the objective of performance optimization with a limited hardware and software cost. We define the metric values for partitioning and develop a cost function that guides partitioning towards the desired objective. We consider minimization of communication cost and improvement of the overall parallelism as essential criteria during partitioning. Two heuristics for hardware/software partitioning, formulated as a graph partitioning problem, are presented: one based on simulated annealing and the other on tabu search. Results of extensive experiments, including real-life examples, show the clear superiority of the tabu search based algorithm.     

一种改进的FCM检索结果聚类算法研究

针对检索引擎返回的查询结果数量巨大,用户难以在较短的时间获取有用的信息,传统FCM聚类算法的距离无法完全准确描述文本间的相似程度,本文提出了一种新的文本间的距离定义,改进了模糊C均值聚类(FCM)聚类算法,利用新改进的算法对搜索引擎返回的结果进行聚类,方便了用户查询。实验证明了算法的可行性与有效性。     

视觉采样聚类方法VSC

基于视觉采样原理,该文提出了一般化的视觉采样聚类方法VSC。该方法将视觉原理与著名的Weber定律结合起来,其特点是：对聚类初始条件不敏感;Weber定律提供了新的聚类有效性标准,并且该方法所得到的合理的聚类数可以依据Weber定律而得到。大量的实验结果表明了算法VSC的有效性。文中讨论了算法VSC与由Yang Miin-Shen等人(2004)新近提出的基于相似度量的聚类算法SCA之间的内在联系,得出了这两个算法具有一定的同解性质,从而揭示了该文所提方法VSC能够有效地克服算法SCA中参数 不易确定的困难。