摘要
为了解决约束优化问题,采用一种基于群智能算法优化的多约束问题优化方法。首先构造同时计及约束条件和优化适应度的目标函数,然后分别利用粒子群算法和人工蜂群算法优化其函数,从而获得约束条件下的优化解。仿真结果表明,该多约束问题优化方法是可行性的,人工蜂群算法比粒子群算法具有更好的搜索和收敛能力。
In order to solve the problem of constraint optimization,a multi-constraint optimization method based on swarm intelligence optimization algorithm is adopted.This method first constructs an objective function that takes into account both constraint condition and optimization fitness,and then the function is optimized by particle swarm algorithm and artificial bee colony algorithm respectively to obtain the optimized solution under the constraint condition.The simulation results of the test function show the feasibility of the multi-constraint optimization method proposed in this paper.In addition,the artificial bee colony algorithm has better search and convergence ability than the particle swarm algorithm.
作者
郜怀通
王荣杰
曾广淼
刘文霞
GAO Huaitong;WANG Rongjie;ZENG Guangmiao;LIU Wenxia(School of Marine Engineering,Jimei University,Xiamen 361021,China;Fujian Province Key Laboratory of Naval Architecture and Marine Engineering,Xiamen 361021,China)
出处
《集美大学学报（自然科学版）》
CAS
2021年第1期56-65,共10页
Journal of Jimei University：Natural Science
基金
国家自然科学基金项目(51879118)
福建省科技拥军项目(B19101)
福建省高等学校新世纪优秀人才支持计划(B17159)
农业部渔业装备与工程技术重点实验室基金项目(2016002,2018001)
人工智能四川省重点实验室基金项目(2017RJY02)
江苏省输配电装备技术重点实验室项目(2017JSSPD01)。
关键词
人工蜂群算法
粒子群算法
约束函数
artificial bee colony algorithm
particle swarm optimization algorithm
constraint function
