Coordinating metaheuristic agents with swarm intelligence

Coordination of multi agent systems remains as a problem since there is no prominent method suggests any universal solution. Metaheuristic agents are specific implementations of multi-agent systems, which imposes working together to solve optimisation problems using metaheuristic algorithms. An idea for coordinating metaheuristic agents borrowed from swarm intelligence is introduced in this paper. This swarm intelligence-based coordination framework has been implemented as swarms of simulated annealing agents collaborated with particle swarm optimization for multidimensional knapsack problem. A comparative performance analysis is also reported highlighting that the implementation has produced much better results than the previous works.     

A stochastic neighborhood search approach for airport gate assignment problem

An appropriate and efficient gate assignment is of great importance in airports since it plays a major role in the revenue obtained from the airport operations. In this study, we have focused mainly on maximum gate employment, or in other words minimize the total duration of un-gated flights. Here, we propose a method that combines the benefits of heuristic approaches with some stochastic approach instead of using a purely probabilistic approach to top-down solution of the problem. The heuristic approaches are usually used in order to provide a fast solution of the problem and later stochastic searches are used in order to ameliorate the previous results of the heuristic approach whenever possible. The proposed method generates an assignment order for the whole planes that corresponds to assignment priority. The ordering process is followed by the allocation step. Since, in practice, each airport has its own physical architecture, there have been arisen many constraints mainly concerning airplane types and parking lots in this step. Sequentially handling the plane ordering and allocation phases provides us great modularity in handling the constraints. The effectiveness of the proposed methodology has been tried to be illustrated firstly on fictively generated flight schedule data and secondly on the real world data obtained from a real world application developed for ?stanbul Atatürk Airport.     

Natural frequencies of a flat viaduct road part simply supported on two ends

Viaduct roads have wide application in big cities with high traffic loads, in order to decrease traffic density and to connect subways to highways. Viaduct roads are constructed using steel structures instead of concrete ones in areas of earthquake risks. The low weight of steel structures however causes problems such as vibration and noise. There is increasing demand especially in populated areas to suppress vibration and noise on highway roads for reducing noise-related environmental pollution. In this study, bending vibrations of rectangular plate viaduct roads, which are supported by six fixed elements of rectangular cross-sectional elements are considered. Natural frequencies are obtained using the Rayleigh-Ritz technique, finite elements analysis, experimentally and neural networks (NN).     

高新技术产业化的风险分析与防范对策

高新技术产业化过程中的风险因素严重影响了高新技术产业化的顺利实施．通过分析高新技术产业化的基本特征和风险的主要类型及其成因，提出了防范风险的对策。     

基于扩展Petri网的PPCES建模研究

针对Job—shop型生产系统中NP难度的调度问题，利用生产计划与控制专家系统(PPCES)进行启发式搜索，根据Petri网建模原理及PPCES的推理需要，对生产系统建模，定义了一类扩展有色、时间Petri网．实践证明，这种方法不仅可以在增强模型描述能力的同时有效地降低其复杂度，还可以应用专家系统领域的知识指导系统进行冲突消解，从而避免了常规分析方法所带来的组合爆炸问题．     

基于LotusDomino群件的工作流管理信息系统开发

关键业务的应用开发离不开工作流技术的支持。通过对工程项目管理系统的需求分析 ,利用LotusDomino提供的工作流驱动引擎开发了一种基于工作流技术的管理信息系统 ,以“推出”的方式将待处理业务呈现在用户面前 ,实现了工作流自动化     

基于AI的主动数据挖掘技术在网络故障管理中的应用

讨论了基于人工智能的主动空间数据挖掘技术在故障管理中的应用，给出了一个应用模型，其中主动空间数据挖掘技术主要体现在数据融合，数据挖掘和知识发现的过程中，文中首先给出了规则定义和触发器定义，并对专家系统的知识发现过程给出了基于时间窗口的告警关联算法，最后给出了在仿真环境下的系统性能测试分析，模型实现和分析数据表明该模型是的可行的。     

一种基于主动网络的高效的网络管理模型

首先分析了传统网管的各种弊端，然后在研究主动网技术和基于策略管理的基础上．提出了一种基于策略管理的主动式网管逻辑体系结构来实现高效的分布式网络管理．该网管模型集中了主动网技术和策略管理的优点．同时克服了策略管理的缺点；可实现管理策略实施的自动化，管理策略定义和传播机制的共享；为定制动态的网管服务提供了支撑．通过仿真实验表明基于该逻辑结构网管系统不仅能够较好地解决传统网管的弊端，同时在性能方面也有所提高．