摘要
针对基本萤火虫算法存在收敛速度慢、易陷入局部最优等缺点,提出一种改进的萤火虫算法用于求解约束优化问题。该算法首先利用混沌序列初始化萤火虫的位置,引入动态随机局部搜索以加快算法的收敛速度;为了避免算法陷入局部最优,对当前全局最优解进行多样性变异操作。对几个数值优化和工程优化问题进行实验。研究结果表明:与其他启发计算法相比,该算法具有较强的寻优性能。
Firefly algorithm（FA） has a few disadvantages in the global searching, including slow convergence speed and high possibility of being trapped in local optimum. An improved FA was proposed to solve constrained optimization problems. Firstly, chaotic sequence was used to initiate firefly position. Secondly, dynamic random local search technique was introduced to improve speed of convergence; thirdly, a diversity mutation operator was given on the global optimum of each generation, thus the algorithm could effectively jump out of local minima. The experimental results and comparisons with other meta-heuristic methods using a set of numerical and engineering optimization problems show that the proposed algorithm is an effective method.
出处
《中南大学学报（自然科学版）》
EI
CAS
CSCD
北大核心
2015年第4期1260-1267,共8页
Journal of Central South University:Science and Technology
基金
国家自然科学基金资助项目(61463009)
贵州省科学技术基金资助项目(黔科合J字[2013]2082号)~~
关键词
萤火虫算法
约束优化问题
动态随机局部搜索
工程优化
firefly algorithm
constrained optimization problem
dynamic random local search
engineering optimization
