An ANTS algorithm for the minimum-span frequency-assignment problem with multiple interference

The frequency-assignment problem is concerned with the assignment of discrete channels to the transmitters of a radio network. Separation of the frequencies assigned to transmitters is necessary to avoid interference. However, unnecessary separation causes an excess requirement for spectrum, the cost of which may be very high. The aim of the work is to minimize the frequency spectrum required for a given level of reception quality over the network. In contrast to the majority of the work presented in the literature, the model chosen to formalize the problem takes multiple interference into consideration. This should provide a better approximation of reality. The method proposed to solve this problem is an approximate nondeterministic tree search (ANTS) algorithm, which is a metaheuristic algorithm based on a computational paradigm inspired by the way real ant colonies function.     

用EDA和禁忌搜索算法进行文本聚类

基于VSM的文本聚类忽略了文本关键词稀疏带来的相似度漂移问题和关键词之间的语义信息和各维度之间的关系,致使文本的相似度计算不精确,文中对相似度计算方法 TF-IDF进行了改进,并提出一种新的聚类方法,利用分布式估计算法和禁忌搜索算法进行聚类,融合分布式估计算法的收敛速度快和禁忌搜索算法能跳出局部搜索的优点,首先对文本进行预处理,然后用分布式估计算法和禁忌搜索算法聚类,既能快速聚类又能防止聚类收敛到局部最优。测试结果表明这种算法行之有效。     

用EDA和禁忌搜索算法进行文本聚类

基于VSM的文本聚类忽略了文本关键词稀疏带来的相似度漂移问题和关键词之间的语义信息和各维度之间的关系,致使文本的相似度计算不精确,文中对相似度计算方法TF—IDF进行了改进,并提出一种新的聚类方法,利用分布式估计算法和禁忌搜索算法进行聚类,融合分布式估计算法的收敛速度快和禁忌搜索算法能跳出局部搜索的优点,首先对文本进行预处理,然后用分布式估计算法和禁忌搜索算法聚类,既能快速聚类又能防止聚类收敛到局部最优。测试结果表明这种算法行之有效。     

求解DEC-POMDP问题的改进遗传算法

分布式部分可观测马尔科夫模型(Decentralized partially observable Markov decision progress,DEC-POMDP)是研究不确定性情况下多主体协同决策的重要模型。由于其求解难度是NEXP-complete,所以迄今为止尚没有有效的算法能求出其最优解。但是存在一部分近似求解的算法可以解决规模较小的问题。针对此问题,在遗传算法的基础上,通过引入最佳起始状态和最佳收益状态提出改进的遗传算法(Improved Genetic Algorithms,IGA),算法将问题的求解分为两个步骤,首先求解从给定起始状态到最佳起始状态的近似最优策略,然后求解在最佳收益状态之间转换的策略。通过实验可以看出IGA压缩了要搜索的策略空间,减小了编码长度,是求解DEC-POMDP的有效算法。     

An improved Cuckoo search localization algorithm for UWB sensor networks

Wireless Networks - Conventional Cuckoo search (CS) localization method can obtain good positioning results that are highly accurate and robust. However, its positioning performance is constrained...     

An improved floating-random-walk algorithm for solving themulti-dielectric Dirichlet problem

An improved floating-random-walk algorithm for solving the multidielectric Dirichlet problem is outlined. The improvement is achieved by using statistically generated Green's functions that are calculated beforehand and stored as lookup tables. These tables have been used to solve the multidielectric Dirichlet problem for an arbitrary two-dimensional geometry. The improved algorithm is also compared with the conventional floating-random-walk algorithm and is found to be at least two times more efficient. Results are presented for two types of parallel-plate geometries     

一种约束布局求解算法的改进

针对一个实际问题,讨论了一种约束布局的启发式算法,提出了约束布局求解的启发式规则及相应的布局方案求解策略,改进后的算法具有很强的灵活性和柔性,同时还对该算法的实际性能进行了仿真,结果表明了改进算法的有效性和合理性.     

A tabu search algorithm for routing optimization in mobile ad-hoc networks

In this paper, we propose a routing optimization algorithm to efficiently determine an optimal path from a source to a destination in mobile ad-hoc networks. To determine an optimal path for the nodes is important for transmitting data between nodes in densely deployed networks. In order to efficiently transmit data to its destination, the appropriate routing algorithms must be implemented in mobile ad-hoc networks. The proposed algorithm is designed by using a tabu search mechanism that is a representative meta-heuristic algorithm. The proposed tabu search algorithm carries out two neighborhood generating operations in order to determine an optimal path and minimize algorithm execution time. We compare the proposed tabu search algorithm with other meta-heuristic algorithms, which are the genetic algorithm and the simulated annealing, in terms of the routing cost and algorithm execution time. The comparison results show that the proposed tabu search algorithm outperforms the other algorithms and that it is suitable for adapting the routing optimization problem.     

A tabu search heuristic for the routing and wavelength assignment problem in optical networks

This letter proposes a tabu search heuristic for solving the routing and wavelength assignment (RWA) problem in optical WDM networks, considering the wavelength continuity constraint and a given set of connections to satisfy. For a number of available wavelengths on each link, this algorithm attempts to maximize the number of routed connections. The algorithm has been implemented and tested on NSFNET and EONNET networks and comparisons have been done with other algorithms in terms of the blocking rate. Generally, the results obtained with our tabu search heuristic are better than those provided by these algorithms.     

一种新的基于禁忌搜索的静态波长路由算法

基于禁忌搜素的基本原理,提出了一种新的静态波长路由智能算法,实现了路由、波长的同时分配.文中给出了算法的流程和实现的细节描述,并且利用常用的四种实际网络模型进行算法仿真.仿真结果表明新算法稳定、有效,能够在合理的时间之内得到比以往的一些算法更优的结果.     

A new method for adaptive IIR filter design based on tabu search algorithm

Adaptive digital filters have proven their worth in a wide range of applications such as channel equalisation, noise reduction, echo cancelling, and system identification. These filters can be broadly classified into two groups: finite impulse–response (FIR) and infinite impulse–response (IIR) filters. IIR filters have become the target of increasing interest because these filters can reduce the filter order significantly as compared to FIR filters. Tabu search is a heuristic optimisation algorithm which has been originally developed for combinatorial optimisation problems. It simulates the general rules of intelligent problem solving and has the ability of discovering the global minima in a multi-modal search space. In this work, a novel method based on tabu search is described for the design of adaptive IIR filters.     

A tabu search heuristic for the routing and wavelength assignment problem in multigranular optical networks

This paper proposes a tabu search heuristic for solving the routing and wavelength assignment problem in multigranular optical networks, considering the wavelength-continuity constraint and a set of connections to satisfy. For a number of fibers per link, a number of wavebands per fiber, and a number of wavelengths per waveband, this algorithm attempts to minimize the total number of ports used in the network by efficiently grouping lightpaths into bands and fibers, and switching the whole bands and fibers. The algorithm has been implemented and tested on the NSFNET network, and comparisons have been made with the Balanced Path Routing and Heavy Traffic First (BPHT) algorithm in terms of number of ports. Generally, the results obtained with our tabu search heuristic are better than those provided by this algorithm.

Using tabu search to solve the Steiner tree-star problem in telecommunications network design

We present a study of using tabu search to solve a specific network design problem arising in the telecommunication industry. We develop a tabu search heuristic for this problem that incorporates long-term memory and probabilistic move selections. Computational results show that the new heuristic consistently outperforms the best local search currently available, with significantly increased performance differences on more difficult problems.This research was supported in part by Air Force Office of Scientific Research AASERT Grant No. F49620-92-J-0248-DEF.     

基于禁止搜索的非线性时间匹配优化算法

动态时间规整算法DTW(Dynamic Time Warping)作为一种非线性时间匹配技术已成功地应用于语音识别系统中。DTW算法使用动态规划技术来搜索两个时间序列的最优规整路径,虽然这种算法计算量小,运算时间较短,但只是一种局部优化算法。禁止搜索TS(Tabu Search)算法是一种具有短期记忆的广义启发式全局搜索技术,适用于解决许多非线性优化问题。本文将该技术用于语音识别系统中,提出了基于禁止搜索的非线性时间规整的优化算法TSTW,使得时间规整函数尽可能逼近全局最优。仿真结果表明,TSTW比DTW有更高的识别率,且运行时间比遗传时间规整算法GTW大大减少。     

改进遗传算法在DOA搜索中的应用

在对短时、低信噪比信号测向时。加权子空间测向算法（WSF）的统计性能优于Music,Esprit等测向算法,且可以对相干信号进行检测。但是因为算法实现涉及到非线性多维搜索。因此运算量很大。本文提出的改进遗传算法,是一种运算速度较快的加权子空间算法的实现算法。该算法将免疫算法引入遗传算法中,并与MVP算法相结合。解决了普通遗传算法（CGA）在DOA搜索中易早熟。后期搜索效率低的问题,拥有快速、全局的搜索能力。计算机仿真证明了该算法的有效性和鲁棒性。     

Novel round-robin tabu search algorithm for prostate cancer classification and diagnosis using multispectral imagery.

Quantitative cell imagery in cancer pathology has progressed greatly in the last 25 years. The application areas are mainly those in which the diagnosis is still critically reliant upon the analysis of biopsy samples, which remains the only conclusive method for making an accurate diagnosis of the disease. Biopsies are usually analyzed by a trained pathologist who, by analyzing the biopsies under a microscope, assesses the normality or malignancy of the samples submitted. Different grades of malignancy correspond to different structural patterns as well as to apparent textures. In the case of prostate cancer, four major groups have to be recognized: stroma, benign prostatic hyperplasia, prostatic intraepithelial neoplasia, and prostatic carcinoma. Recently, multispectral imagery has been used to solve this multiclass problem. Unlike conventional RGB color space, multispectral images allow the acquisition of a large number of spectral bands within the visible spectrum, resulting in a large feature vector size. For such a high dimensionality, pattern recognition techniques suffer from the well-known "curse-of-dimensionality" problem. This paper proposes a novel round-robin tabu search (RR-TS) algorithm to address the curse-of-dimensionality for this multiclass problem. The experiments have been carried out on a number of prostate cancer textured multispectral images, and the results obtained have been assessed and compared with previously reported works. The system achieved 98%-100% classification accuracy when testing on two datasets. It outperformed principal component/linear discriminant classifier (PCA-LDA), tabu search/nearest neighbor classifier (TS-1NN), and bagging/boosting with decision tree (C4.5) classifier.     

一种改进的Steiner树启发式算法

最小Steiner树问题是NP完全问题，关于Steiner问题的启发式算法的研究具有重要理论和实际意义。本文在MPH算法基础上，对于经过某些关键节点的短路径优先考虑，提出了KBMPH算法，从而实现更多链路的共享。在随机网络上的仿真结果表明，极大多数情况下，在准Steiner树的网络费用KBMPH算法优于MPH算法，KBMPH算法的复杂度为O（n^3）。     

An improved algorithm for coherent-system reliability

This paper presents a simpler and more efficient algorithm (LVT), based on the one proposed by Veeraraghavan and Trivedi (VT), to calculate system reliability using `sum of disjoint products' and `multiple variable inversion' (MVI) techniques. A proposition, a state space division idea, and a theorem are introduced. To compare LVT with several well known MVI algorithms (viz. VT, KDH88, CAREL) the 4 algorithms are implemented on the same platform (Solaris), and the execution-time comparison shows the computational saving achieved by LVT is appreciable