欢迎您！东篱公司
退出
-
申报数据库
-
立项数据库
-
成果数据库
-
项目获奖数据库
中文摘要：
通过将粒子群优化算法（PSO）与经典局部一维搜索技术相结合，提出一种嵌入局部一维搜索技术的混合粒子群优化算法（LLS—PSO）。该算法在基本粒子群优化算法中引入一维搜索技术，选取最优粒子进行局部一维搜索，增强了在最优点附近的局部搜索能力，以加快算法的收敛速度。对三个经典复杂优化问题进行数值实验，并与基本PSO算法进行比较。实验分析和结果表明，LLS-PSO具有更好的优化性能。
英文摘要：
This paper proposed a new hybrid particle swarm optimization algorithm based on co-line search technique by integrating local line search technique and basic particle swarm optimization. In the LLS-PSO algorithm, it would introduce one dimension search technique based on elementary particle algorithm, select the best population for local search to speed up the convergence rate of the algorithm. The performance of the algorithm tested using three typical nonlinear optimization problem was reported and compared with that of basic PSO. Results show that performance of LLS-PSO algorithm is much better than basic PSO.
同期刊论文项目
同项目期刊论文
位置：