搜索资源列表
pso
- 简单粒子群算法 能优化但目标函数 算法简单 效果好-A simple particle swarm optimization algorithm to optimize the objective function, but simple and good results
zlbPSO
- 多目标粒子群的基本源代码，两个目标的源代码-Multi-objective particle swarm basic source code, source code in two target
cmopso
- 云多目标粒子群算法，基于matlab环境，可供学习者参考。-Cloud multi-objective particle swarm algorithm, based on the Matlab environment available to learners.
fmopso
- 模糊多目标粒子群算法，基于matlab环境，可供学习者参考。-Fuzzy multi-objective particle swarm algorithm, based on the Matlab environment for learners Reference.
NSGA-II
- 运行数据是吸纳粒子群算法的精华，是先多目标优化。-Run data to absorb the essence of the particle swarm algorithm is the first multi-objective optimization.
PSOGSA
- 程序提出了一种基于人群混合算法，是粒子群优化和引力搜索算法的组合。主要目标提高整合PSO和GSA算法的能力-Hybrid Particle Swarm Optimization and Gravitational Search Algorithm (PSOGSA) A new hybrid population-based algorithm (PSOGSA) is proposed with the combination of Particle Swarm Optimization
mopso
- 基于扩展粒子群算法的群机器人多目标搜索，引入动态闭环任务分工，能够并行搜索，提高搜索效率。-Particle swarm optimization algorithm based on extended multi-target search robot group, introducing dynamic closed-loop division of tasks in parallel searches, improve search efficiency.
m-particle-swarm-optimization
- 多目标粒子群算法，在基本粒子群算法的基础上进行了改进，程序简单明了。-Multi-objective particle swarm algorithm based on particle swarm algorithm has been improved, the program is simple and straightforward.
PSO
- 利用粒子群算法，实现简单的单目标物资分配问题-Using particle swarm optimization to achieve a simple single objective optimization
matlabPSO
- 提出了一种新的多目标粒子群优化(MOPSO)算法，该算法采用自适应网格方法来估计非劣解集中粒子的密度信息、平衡全局和局 部搜索能力的 Pareto 最优解的搜索机制、删除品质差的多余粒子的 Archive 集的修剪技术。通过对三峡梯级多目标优化调度问题的计算， 表明该算法是求解大规模复杂多目标优化问题的一种有效手段。-A new multi-objective particle swarm optimization(MOPSO) is proposed. The proposed alg
新建文件夹
- 提出了一种以目标函数变化量作为评价函数的改进禁忌搜索算法,并进行了理论分析,然后将其与有效禁忌搜索算法作了性能比较。通过比较三个公共测试数据集的计算结果,验证了本文提出的禁忌搜索算法的可行性和有效性。(Proposed a change in the objective function as the evaluation function of the improved tabu search algorithm, and has carried on the theoretical anal
main
- 采用多目标粒子群算法求解多目标背包问题 问题：假设存在五类物品，每类物品又包含四种具体物品，要求从五类物品中分别选择一种放入背包，使得背包总价值最大，总体积最小，总质量不超过92kg(The problem is solved by multi objective particle swarm optimization algorithm, multi-objective knapsack problem: suppose there are five categories of goods,
DCPSO
- 标准粒子群算法介绍，目标函数求极值仿真，同时改进型的粒子群算法，避免陷入局部收敛(Improved particle swarm algorithm to avoid falling into local convergence.)