双种群鱼群算法在分布式投资组合的应用

doi:10.16182/j.issn1004731x.joss.20-0389

系统仿真学报 ›› 2021, Vol. 33 ›› Issue (9): 2074-2084.doi: 10.16182/j.issn1004731x.joss.20-0389

双种群鱼群算法在分布式投资组合的应用

王付宇, 汤涛

安徽工业大学管理科学与工程学院,安徽马鞍山 243032

收稿日期:2020-06-22 修回日期:2020-08-02 出版日期:2021-09-18 发布日期:2021-09-17
作者简介:王付宇(1977-)，男，博士，教授，研究方向为生产运作管理、智能优化算法。E-mail：xiaowang96@163.com
基金资助:
国家自然科学基金(71872002); 教育部人文社会科学青年基金(19YJCZH091); 安徽省哲学社会科学规划(AHSKY2018D15); 安徽普通高校重点实验室开放基金(CS2019-ZD02)

Application of Two-population Fish Swarm Algorithm in Distributed Portfolio

Wang Fuyu, Tang Tao

School of Management Science and Engineering, Anhui University of Technology, Ma'anshan 243032, China

Received:2020-06-22 Revised:2020-08-02 Online:2021-09-18 Published:2021-09-17

摘要/Abstract

摘要： 针对人工鱼群算法优化精度不高和易陷入局部最优等缺点,结合引力算法和教学优化的思想,提出了一种双种群鱼群搜索算法。引入交叉思想,对双种群得出的结果进行交叉再取优,为了避免陷入局部最优,加入模拟退火的Metropoils准则。通过标准函数对算法进行验证,结果表明：双种群鱼群算法寻优效果要优于传统人工鱼群算法和已知文献算法。在已知文献基础上提出了一种分布式投资组合模型,并将设计算法应用于该进行求解,验证了该算法求解离散组合优化问题的有效性。

关键词: 双种群鱼群算法, 引力搜索, 教学优化, 分布式投资组合问题

Abstract: Aiming at the disadvantages of artificial fish swarm algorithm, such as low precision and easily falling into local optimum, combining the idea of gravity algorithm and teaching optimization, a two-population fish swarm search algorithm is proposed. Cross-thinking is adopted to optimize the results obtained by the two populations and avoid the local optimization. Metropoils criterion of simulated annealing is added to the standard function verifies the algorithm, and the results show that the two-population fish swarm algorithm is better than the traditional artificial fish swarm algorithm and the known literature algorithm. Based on the known literature, a distributed portfolio model is proposed, in which the design algorithm is applied to solve the distributed portfolio model, and verifies the effectiveness of the algorithm in solving the discrete portfolio optimization problem.

Key words: two-population fish swarm algorithm, gravitational search, teaching optimization, distributed portfolio problems

中图分类号:

TP301.6
TP18

王付宇, 汤涛. 双种群鱼群算法在分布式投资组合的应用[J]. 系统仿真学报, 2021, 33(9): 2074-2084.

Wang Fuyu, Tang Tao. Application of Two-population Fish Swarm Algorithm in Distributed Portfolio[J]. Journal of System Simulation, 2021, 33(9): 2074-2084.

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双种群鱼群算法在分布式投资组合的应用

Application of Two-population Fish Swarm Algorithm in Distributed Portfolio

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