Flower pollination algorithm based on simulated annealing

doi:10.11772/j.issn.1001-9081.2015.04.1062

Journal of Computer Applications ›› 2015, Vol. 35 ›› Issue (4): 1062-1066.DOI: 10.11772/j.issn.1001-9081.2015.04.1062

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Flower pollination algorithm based on simulated annealing

XIAO Huihui^1,2, WAN Changxuan¹, DUAN Yanming², ZHONG Qing¹

1. School of Information Technology, Jiangxi University of Finance and Economics, Nanchang Jiangxi 330013, China;
2. College of Computer and Information Engineering, Hechi University, Yizhou Guangxi 546300, China

Received:2014-11-16 Revised:2014-12-22 Online:2015-04-10 Published:2015-04-08

基于模拟退火的花朵授粉优化算法

肖辉辉^1,2, 万常选¹, 段艳明², 钟青¹

1. 江西财经大学信息管理学院, 南昌 330013;
2. 河池学院计算机与信息工程学院, 广西宜州 546300

通讯作者: 段艳明
作者简介:肖辉辉(1977-),男,江西吉安人,讲师,博士研究生,主要研究方向:智能计算、数据挖掘、情感计算; 万常选(1962-),男,江西南昌人,教授,博士生导师,博士,主要研究方向:Web数据管理、情感计算、数据挖掘、信息检索; 段艳明(1978-),女,江西吉安人,讲师,硕士,主要研究方向:智能计算; 钟青(1991-),女,江西赣州人,硕士研究生,主要研究方向:数据挖掘、情感计算。
基金资助:
国家自然科学基金资助项目(61173146);广西自然科学基金资助项目(2013GXNSFBA019022);广西新世纪教改项目(2013JGA217, 2014JGA211);河池学院青年科研课题(2012B-N005, 2012B-N007);河池学院教育教学改革项目(2014EB022)。

Abstract

Abstract:

A hybrid algorithm of Simulated Annealing (SA) and flower pollination algorithm was presented to overcome the problems of low-accuracy computation, slow-speed convergence and being easily relapsed into local extremum. The sudden jump strategy in SA was utilized to avoid falling into local optimum, and the global searching performance of SA was exploited to enhance the global searching ability of the hybrid algorithm. The hybrid algorithm was tested through six standard functions and compared to basic Flower Pollination Algorithm (FPA), Bat Algorithm (BA), Particle Swarm Optimization (PSO) algorithm and improved PSO algorithm. The simulation results show that the optimal value of 4 functions were found by the hybrid algorithm with better convergence precision, convergence rate and robustness. At the same time, the experimental results of solving nonlinear equation group verify the validity of the hybrid algorithm.

Key words: Flower Pollination Algorithm (FPA), optimization performance, nonlinear equations, simulated annealing, fitness

摘要：

针对花朵授粉算法寻优精度低、收敛速度慢、易陷入局部极小的不足,提出一种把模拟退火(SA)融入到花朵授粉算法中的混合算法。该算法通过SA的概率突跳策略使其避免陷入局部最优,并利用SA的全域搜索的性能增强算法的全局寻优能力。通过6个标准测试函数进行测试,仿真结果表明,改进算法在4个测试函数中能够找到理论最优值,其收敛精度、收敛速度、鲁棒性均比基本的花朵授粉算法(FPA)、蝙蝠算法(BA)、粒子群优化(PSO)算法及改进的粒子群算法有较大的提高;同时,对非线性方程组问题进行求解的算例应用也验证了改进算法的有效性。

关键词: 花朵授粉算法, 寻优性能, 非线性方程组, 模拟退火, 适应度

CLC Number:

TP301.6

XIAO Huihui, WAN Changxuan, DUAN Yanming, ZHONG Qing. Flower pollination algorithm based on simulated annealing[J]. Journal of Computer Applications, 2015, 35(4): 1062-1066.

肖辉辉, 万常选, 段艳明, 钟青. 基于模拟退火的花朵授粉优化算法[J]. 计算机应用, 2015, 35(4): 1062-1066.

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Flower pollination algorithm based on simulated annealing

基于模拟退火的花朵授粉优化算法

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