Max-min ant system ( MMAS) has great ability of searching the whole best solution and availability of avoiding premature convergence, but at the same time there is defect of slow speed of convergence. 最大-最小蚂蚁系统(MMAS)具有较强的全局最优解搜索能力,能够有效避免早熟收敛,但收敛速度较慢。
A max-min ant system based on simulated annealing is presented. 介绍了一种基于模拟退火策略的最大-最小蚂蚁系统。
A novel method for Robot's path planning based on ant max-min ant system 一种新的基于MMAS的机器人路径规划方法
Application of heuristic max-min ant system with mutation operator to flow shop scheduling problem 带变异算子的启发式最大最小蚂蚁系统求解流水车间调度问题
In the paper, max-min ant system ( MMAS) added the ability of smell is applied for the routing problem of coarse-grained reconfigurable architecture. 以最大-最小蚁群系统为基础,为蚁群采用增加了嗅觉分辨能力,应用于粗粒度可配置结构芯片的路由问题。
By spatially area-encoding fuzzy matrices, the max-min composed operation needed by fuzzy associative memory is realized in a multiple-imaging system. 通过面积编码模糊矩阵,在多重成像系统下实现了模糊关联存贮器所需的最大一最小合成运算。
MAX-MIN ant system algorithm is one of the best approaches to resolve the traveling salesman problem and the quadratic assignment problem. MAX-MIN蚂蚁系统算法是解决旅行商问题及二次分配问题的最好方法之一。
Simulation results show that this algorithm which searches for the best path average solution is shorter than ant system and max-min ant system. 仿真结果表明,该算法搜索到最佳路径平均解比蚂蚁系统和最大最小蚂蚁系统均有缩短。
In this paper, Max-Min Ant Colony System is taken as the main algorithm for this system, which can transform problems with constrains to problems without constrains and simplify problem, so that makes great conveniences for solving problems. 选择最大&最小蚁群系统作为核心控制算法,将有约束条件的问题转化为无约束的数学问题,使问题简单化,为问题的解决提供了便利条件。
To solve this problem, we propose an ant colony optimization algorithm. It is a MAX-MIN ant system combined with a post-optimization procedure, which is implemented in the hyper-cube framework. 构建了求解问题的蚁群优化算法,该算法是一个集成了后优化过程的在超立方框架下执行的MAX-MIN蚂蚁系统。
It is a MAX-MIN ant system hybridized with tabu search, which is implemented in the hyper-cube framework. Additionally, a post-optimization procedure is incorporated to further improve the best-found solutions. 该算法主体是一个在超立方框架下执行的MAX-MIN蚂蚁系统,算法混合了禁忌搜索算法作为局部优化算法,同时集成了一个后优化过程来进一步优化最优解。
Genetic algorithms are discussed in two areas: discrete space and continuous space. Max-Min Ant System algorithm, which could be used in real soccer robot system by optimizing the environment model, is introduced. 其中遗传算法分为离散空间和连续空间两种情况来详细讨论,蚁群算法则对环境模型进行了优化得到了适用于实际情况的最大最小蚂蚁系统算法。