基于粒子群优化的模糊聚类分析

基于求解实优化问题时,粒子群优化算法优于遗传算法。在基于遗传算法的模糊C均值聚类算法基础上,给出了基于粒子群的模糊C均值聚类算法,试验结果表明:该算法克服了传统的模糊C均值聚类算法的缺陷,同时在收敛速度方面明显优于基于遗传算法的模糊C均值聚类算法。     

Generalized linear mixed models with informative dropouts and missing covariates

Generalized linear mixed models (GLMM) are useful in many longitudinal data analyses. In the presence of informative dropouts and missing covariates, however, standard complete-data methods may not be applicable. In this article, we consider a likelihood method and an approximate method for GLMM with informative dropouts and missing covariates. The methods are implemented by Monte–Carlo EM algorithms combined with Gibbs sampler. The approximate method may lead to inconsistent estimators but is computationally more efficient than the likelihood method. The two methods are evaluated via a simulation study for longitudinal binary data, and appear to perform reasonably well. A dataset on mental distress is analyzed in details.     

On Minimally-supported <Emphasis Type="Italic">D</Emphasis>-optimal Designs for Polynomial Regression with Log-concave Weight Function

This paper studies minimally-supported D-optimal designs for polynomial regression model with logarithmically concave (log-concave) weight functions. Many commonly used weight functions in the design literature are log-concave. For example, and exp(−x ²) in Theorem 2.3.2 of Fedorov (Theory of optimal experiments, 1972) are all log-concave. We show that the determinant of information matrix of minimally-supported design is a log-concave function of ordered support points and the D-optimal design is unique. Therefore, the numerically D-optimal designs can be constructed efficiently by cyclic exchange algorithm.     

18-run nonisomorphic three level orthogonal arrays

In this paper we construct all possible orthogonal arrays OA(18,q, 3,2) with 18 runs and 3 ≤ q ≤ 7 columns and present those that are nonisomorphic. A discussion on the novelty and the superiority of many of the designs found in terms of isomorphism and generalized minimum aberration has been made.      

基于启发式算法的成品油配送计划研究

通过对成品油配送计划特点的研究与分析，建立了成品油配送计划编制的数学模型；并设计了模型求解方案；通过对实验结果的分析，证明本文设计的算法快速、有效、稳定。     

一种基于LSB的改进信息隐藏算法及实现

传统的LSB算法是将私密信息以二进制的形式嵌入到载体像素值的最低有效位,这样对图像的质量负面影响可以降到最小。本文提出了一种将过滤技术与LSB算法相结合的信息隐藏算法。利用过滤技术增强图片质量,利用LSB算法进行私密信息的嵌入。改进型的LSB算法比原算法具有更高信息存储量以及更高信息安全性等优点。     

贪心算法求解最少资源问题的探讨

面对资源的日益紧缺,如何有效合理的利用资源一直是专家学者研究和探讨的热点问题。最少资源问题是对初步资源规划问题的探讨,可以为多个资源组合规划问题的基础研究提供有效的参考作用。传统的回溯法穷举虽然能找到最少资源问题的最优解但其时间复杂度会高于o(n!),往往耗时太多,不能满足问题的及时性。提出了一种以最早开始时间为贪心策略的求解最少资源问题的贪心算法,不仅能够找到最优解,而且其时间复杂度仅为o(n2),极大提高了算法的效率。     

物流中心仓库货位优化系统的设计研究

以上海医药物流中心仓库为研究对象，为其仓库货位优化系统建立一个有效的多目标优化数学模型。并引入“类聚”的方法来解决同一产品族的货物临近放置的问题。最后，应用多目标遗传算法进行货位优化。     

大规模定制下基于交互式遗传算法的谈判模型研究

越来越多的企业已经认识到大规模定制是一种竞争策略,可以给企业带来竞争优势。随着大规模定制程度的提高,企业间对信息交互的及时性、有效性的要求也越来越高,企业迫切需要一种快速高效的谈判解决方案来适应大规模定制的需要。运用交互式遗传算法理论来建立谈判模型,以适应大规模定制的需要。     

A genetic algorithm based approach to transactional and QoS-aware service selection

As there are various risks of failure when Web services are deployed in unreliable environment, the execution of a composite Web service (CWS) requires the transaction mechanism to guarantee its reliable execution. However, the existing service selection approaches consider QoS and transaction separately and have not considered that transactional properties may affect the QoS such as the execution time of a CWS. This work addresses the importance of considering transactional properties and how the transactional properties affect the QoS simultaneously in the process of service selection by a QoS-aware and transactional-aware selection approach. First, a performance evaluation method is proposed to calculate the execution time of a transactional CWS. Then, a genetic algorithm based approach, which takes into account the execution time, price, transactional property and successful execution rate of CWS, is presented to achieve global optimisation service selection. Finally, experimental results show the efficiency and effectiveness of the approach.