搜索资源列表
GCP-PSO
- 運用粒子群搜尋演算法解GCP問題，並瞭解如何解出此問題的源碼-Search using particle swarm algorithm solution GCP issues and learn how to solve this problem source
TSP-ACO
- 運用蟻群演算法ACO去求解TSP旅行者路徑問題-Using ant algorithm to solve TSP travelers ACO path problem
liziqun
- 粒子群优化是一种新兴的基于群体智能的启发式全局搜索算法，粒子群优化算法通过粒子间的竞争和协作以实现在复杂搜索空间中寻找全局最优点。-Particle swarm optimization is a new global search heuristic algorithm based on swarm intelligence, particle swarm optimization algorithm by particle competition and collaboration to a
QPOS
- QPSO量子粒子群算法，改进，防止陷入局部极值，防止早熟-Impoved QPSO
yiqunsuanfa
- 蚁群算法解决TSP问题。通过蚁群算法解决一个城市的结合以及城市之间的旅行代价，寻找经过每个城市一次且仅一次而最终返回的旅行最小代价，及寻找最短路径。-Ant colony algorithm to solve TSP problem. Through the combination of ant colony algorithm to solve a city and cost of travel between cities, seeking after each city once and
yiqunyouhua
- 蚁群算法是受真实的蚂蚁群体行为启发而得出的一类仿生算法。采用蚁群算法，设计好蚁群系统，利用MATLAB进行仿真，解决函数优化问题。-Ant colony algorithm is inspired by real ants swarm behavior and it is concluded that the category of bionic algorithm. Using ant colony algorithm, design good ant colony system, use o
pso_Trelea_vectorized
- 粒子群算法MATLAB程序,求解优化问题。(Particle swarm optimization (PSO) MATLAB program)