快速动态优先搜索树的实现及其应用

对形如（x1：x2,[-∞：y]）的二维查询问题,提出一种快速的、易于实现的动态优先搜索树数据结构及其相关算法,采用只在叶节点存储数据的结构,以及在常数时间内实现旋转操作的算法。设n为数据点的个数,k为满足搜索条件的解的个数,则该动态搜索树空间复杂度为O（n）,插入、删除操作的时间复杂度为O（10gn）,搜索复杂度为O（logn＋k）。     

面向本体的服务组合差分进化策略

针对目前Web服务描述服务功能的语义不够深入而使服务识别组合能力欠佳的问题,提出一种面向本体的语义服务功能描述方法,建立本体间的映射关系模型和服务质量关系模型,通过改进差分进化算法求解,得到一种较好的服务组合识别方法。在九寨沟旅游管理信息系统中的应用表明,该方法比传统的方法优越。     

基于P2P的语义Web服务发现机制

分析集中式语义Web服务发现机制存在的问题,利用P2P和本体技术,提出一种基于P2P的语义Web服务发现机制。将服务的部署与发布无缝地绑定在一起,按应用领域和服务目标将整个P2P网络组织成3层结构,基于该结构建立3阶段服务发现算法,达到优化网络结构、提高服务发现效率的目的。     

ATM网络流量控制中的活动VC计算方法

ATM网络ABR业务流量控制是一种基于速率的流量控制机制。在ERICA算法的基础上,提出有效活动虚连接的计算方法,根据它们的活动度计算活动连接的有效数值,从而准确计算出处于活动状态的源端数,将未用带宽在ATM网络ABR连接之间公平且准确地进行分配,体现了Max-Min公平分配准则,能保证算法的高效性和带宽分配的公平性。     

通用的个性化自动谈判服务框架及其实现

针对目前缺少从用户的个性化服务需求到主体服务实现角度设计的通用框架的问题,给出一个通用的个性化自动谈判框架。提出用户个性化服务需求转换为主体服务实现的方法和主体谈判服务的实现步骤,通过一个典型案例的实现与分析结果表明,该框架具有较好的实用性。     

基于层次管理的按需路由协议研究

动态源路由（DSR）协议能较好适用中小型对等自组网络环境,但在非对等网络环境中面临一定应用局限。针对该问题,分析DSR协议的特点和存在问题,结合非对等环境和层次路由思想,提出新的协议CDSR,对CDSR路由协议进行性能评估。仿真结果表明,该协议具有较好的执行效能,可提升网络性能。     

设计模式在民航信息平台中的应用

为了在面向服务设计中有效提高系统的灵活性、敏捷性,以民航综合信息平台为背景,使用设计模式构建面向服务的应用系统。针对民航综合信息平台的核心服务设计,提出服务接口和服务网关2种面向服务的设计模式,将其实现在应用系统中,以验证设计模式在面向服务系统设计中的有效性。     

A comparative study on the performance of dissortative mating and immigrants-based strategies for evolutionary dynamic optimization

Traditional Genetic Algorithms (GAs) mating schemes select individuals for crossover independently of their genotypic or phenotypic similarities. In Nature, this behavior is known as random mating. However, non-random protocols, in which individuals mate according to their kinship or likeness, are more common in natural species. Previous studies indicate that when applied to GAs, dissortative mating - a type of non-random mating in which individuals are chosen according to their similarities - may improve their performance (on both speed and reliability). Dissortative mating maintains genetic diversity at a higher level during the run, a fact that is frequently observed as a possible cause of dissortative GAs’ ability to escape local optima. Dynamic optimization demands a special attention when designing and tuning a GA, since diversity plays an even more crucial role than it does when tackling static ones. This paper investigates the behavior of the Adaptive Dissortative Mating GA (ADMGA) in dynamic problems and compares it to GAs based on random immigrants. ADMGA selects parents according to their Hamming distance, via a self-adjustable threshold value. The method, by keeping population diversity during the run, provides an effective means to deal with dynamic problems. Tests conducted with dynamic trap functions and dynamic versions of Road Royal and knapsack problems indicate that ADMGA is able to outperform other GAs on a wide range of tests, being particularly effective when the frequency of changes is low. Specifically, ADMGA outperforms two state-of-the-art algorithms on many dynamic scenarios. In addition, and unlike preceding dissortative mating GAs and other evolutionary techniques for dynamic optimization, ADMGA self-regulates the intensity of the mating restrictions and does not increase the set of parameters in GAs, thus being easier to tune.     

Minimizing a linear objective function under a fuzzy max-t norm relation equation constraint

The work examines the feasibility of minimizing a linear objective function subject to a max-t fuzzy relation equation constraint, where t is a continuous/Archimedean t-norm. Conventional methods for solving this problem are significantly improved by, first separating the problem into two sub-problems according to the availability of positive coefficients. This decomposition is thus more easily handled than in previous literature. Next, based on use of the maximum solution of the constraint equation, the sub-problem with non-positive coefficients is solved and the size of the sub-problem with positive coefficients reduced as well. This step is unique among conventional methods, owing to its ability to determine as many optimal variables as possible. Additionally, several rules are developed for simplifying the remaining problem. Finally, those undecided optimal variables are obtained using the covering problem rather than the branch-and-bound methods. Three illustrative examples demonstrate that the proposed approach outperforms conventional schemes. Its potential applications are discussed as well.