一种具有遗忘能力的混合型改进量子粒子群算法

A Hybrid Improved Quantum Particle Swarm Optimization Algorithm with Forgetting Ability

受自然遗忘现象的启发,作者提出了一种具有遗忘能力的混合型改进量子粒子群优化算法(HIQPSOF)。在粒子搜索过程中,每个粒子不仅具有遗忘能力,而且还利用HS算法的记忆特征让粒子的遗忘与记忆达到一种动态平衡。最终作者将所提算法与其他几种算法同CEC2013测试套件中的28个基准函数进行性能比较,仿真实验结果证明HIQPSOF在不同类型的函数优化上有较好的性能,也是一种求解精度高,收敛速度快的改进算法。

Inspired by the phenomenon of forgetting that often occurs in natural society, a Hybrid Improved Quantum Particle Swarm Optimization Algorithm(HIQPSOF) with forgetting ability is proposed in this paper. In the process of particle search, each particle not only has the ability of forgetting, but also uses the memory characteristics of Harmony Search(HS) algorithm to make the forgetting and memory of particles reach a dynamic balance process. Finally, we compare the performance of the proposed algorithm and other algorithms with 28 benchmark functions in CEC2013 test suite. The simulation results show that HIQPSOF has good performance in different types of function optimization. It is also an improved algorithm with high accuracy and fast convergence speed.