蚁群算法

改进型蚁群算法求解单任务Agent联盟

Searching for Agent Coalition for Single Task Using Improved Ant Colony Algorithm

然后基于蚁群算法和Web日志数据建立了一个用户导航模型；

Secondly , a navigation model is established based on ant colony approach and web logs .

蚁群算法及其在FlowShop问题和聚类问题上的应用

ACA and Its Application on Flow Shop Problem and Clustering Problem

基于蚁群算法的GIS数据拓扑空间关系描述

Description of Topological Spatial Relationship on GIS Data Based on Ant Colony Algorithms

基于蚁群算法PID控制器的自动配料系统研究

Research on automatic PID controller proportioning system based on ant colony algorithm

基于蚁群算法的智能人工腿最优PID控制器设计

Design of ant algorithm-based optimal PID controller and its application to intelligent artificial leg

求解QoS路由优化的蚁群算法研究

Research on Ant Colony Algorithm for Solving QoS Routing Optimization

应用蚁群算法解决CDMA通信系统中的多用户检测问题。

Ant Colony Optimization Algorithm for the MUD problem in CDMA communication systems .

蚁群算法在WSN路由协议中的应用

Application of Improved Ant Colony Algorithm in WSN Routing Protocol

基于蚁群算法的MAS路网容量仿真模型

A Simulation Model of Road-Network Flows Based on ACO and MAS

基于有功功率平衡和蚁群算法优化PI参数的有源滤波器

Active Power Filter Based on Active Power Balance Principle and Ant Colony Algorithm Optimized PI Regulator

VLSI电路非曼哈顿布局和改进蚁群算法的初步研究

A Preliminary Study of Non-manhattan VLSI Placement and Enhanced ACS

遗传算法和蚁群算法在求解TSP问题上的对比分析

Comparison and analysis of generation algorithm and ant colony optimization on TSP

动态自适应蚁群算法求解TSP问题

Dynamic and adaptive ant colony algorithm for solving TSP problems

蚁群算法解决TSP问题的研究

Ant algorithms for the traveling salesman problem

在ACS基础上，改良的蚁群算法采用了更为高效的信息素更新和路径选择机制，使得改进后算法的全局收敛速度得到明显的提高；

The improved ant colony optimization algorithm is using a new pheromone updating strategy .

仿真结果表明主汽温系统的PID控制器参数经过改进蚁群算法优化后，使得该系统具有良好的跟随性能、抗干扰性能和鲁棒性。

Simulation results show that the system of PID controller parameters optimization used improved ant colony algorithm has a good following performance , anti-jamming performance and robustness .

混合蚁群算法及其用于有机物毒性的QSAR研究

Hybrid ant colony algorithm and its application to QSAR for toxicities of organic substance

蚁群算法（AntColonyAlgorithm，简称ACA）是最近几年才提出来的一种新型的模拟进化算法。

Ant colony ( ant colony algorithm , referred to as ACA ) is raised only in recent years a new type of simulated evolutionary algorithm .

由于蚁群算法的分布式的计算、自组织、信息素的正反馈等特性，蚁群算法被尝试用于adhoc网络的路由计算。

Ant colony algorithms support distributed computing , self-organizing and the positive feedback pheromones , so ant colony algorithms were tried for ad hoc network routing .

蚁群算法作为一类启发式算法，已经成功地应用于求解TSP问题。

Ant colony algorithm is a class of heuristic search algorithms that have been successfully applied to solving NP hard problems .

最初的蚁群算法为解决旅行商问题（TSP）而提出，并在各种离散组合优化问题中展现出良好的获取解的能力，随后逐渐应用到连续优化问题领域中，有着广阔的应用前景。

It was first proposed for solving Traveling Salesman Problem , and exhibited it good ability in solving other combinatorial problem .

基于云模型的小生境MAX-MIN相遇蚁群算法

MAX-MIN meeting ant colony algorithm based on cloud model theory and niche ideology

利用提出的算法对典型的TSP问题进行仿真研究，结果表明比典型蚁群算法在收敛速度和解的性能上都有较大改善。

The simulation results for typical TSP problems demonstrate that the proposed algorithms are more effective than those for other modified ant systems .

介绍了蚁群算法的基本思想与原理，以及在多Agent系统中的设计、实现方法，给出了在多Agent系统环境中的仿真实验结果。

This paper introduces the basic principles of ACA and its method of design and implement in a multiple agent system ( MAS ) . Computer simulation results of MAS based on ACA are discussed in this thesis .

同时，引入多约束Qos路由模型，应用动态自适应最大最小蚁群算法对多约束Qos路由模型进行求解，在满足多Qos约束的条件下，能够快速地找到通信开销最小的链路。

Meanwhile , it introduces a multiple constrained Qos routing model and uses the dynamic adaptive Max-Min ant colony algorithm for multiple constrained Qos routing model to get the best solution .

由于面向WebServices应用集成的问题还是一个新的技术问题，将蚁群算法的应用研究扩展到面向WebServices应用集成对蚁群算法的发展也具有非常重要的意义。

Since the application integrated problem which is oriented towards Web Service is a new technical one , it is of great importance to expand the study of ant colony algorithm from application research to application integrated one oriented towards Web Services .

本文以大功率倒伞曝气机行星减速齿轮箱的体积最小为优化目标函数，建立了行星减速齿轮箱的数学模型，并运用蚁群算法和MATLAB语言，对行星齿轮箱进行了优化计算。

This paper takes the smallest volume of reducing planet gear box as the optimized target function , and establishes mathematical model , and finally uses ant colony algorithm and the MATLAB language to optimize planet gear box .

详细介绍了蚁群算法的基本原理及数学模型，并以TSP问题为例对蚁群算法的实现过程进行了说明。

The principle and mathematical model of ant colony algorithm is deeply analyzed and elucidated . The realization process of ant colony algorithm is explained by solving the TSP problem .

提出了一种改进的蚁群算法，并将其用于求解连续空间函数优化问题和工程控制过程中PID控制器参数优化中的应用，实验证明了此改进算法的可行性。

In this paper , a kind of ACO algorithm have been proposed for solving the continuous space optimization and PID controller parameters optimization in industrial process control . Finally the results obtained via computer simulation show its validity .