[1]郜怀通,王荣杰,曾广淼,等.采用群智能算法的多约束问题优化[J].集美大学学报(自然版),2021,26(1):56-65.
 GAO Huaitong,WANG Rongjie,ZENG Guangmiao,et al.A Method to Deal with Multi Constraint Problems[J].Journal of Jimei University,2021,26(1):56-65.
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采用群智能算法的多约束问题优化()
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《集美大学学报(自然版)》[ISSN:1007-7405/CN:35-1186/N]

卷:
第26卷
期数:
2021年第1期
页码:
56-65
栏目:
船舶与机械工程
出版日期:
2021-01-28

文章信息/Info

Title:
A Method to Deal with Multi Constraint Problems
作者:
郜怀通1王荣杰12曾广淼1刘文霞1
(1.集美大学轮机工程学院,福建 厦门 361021;2.福建省船舶与海洋重点实验室,福建 厦门 361021)
Author(s):
GAO Huaitong1WANG Rongjie12ZENG Guangmiao 1LIU Wenxia1
(1. School of Marine Engineering,Jimei University,Xiamen 361021,China;2.Fujian Province Key Laboratory of Naval Architecture and Marine Engineering,Xiamen 361021,China)
关键词:
人工蜂群算法粒子群算法约束函数
Keywords:
artificial bee colony algorithmparticle swarm optimization algorithmconstraint function
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。
Abstract:
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.
更新日期/Last Update: 2021-03-25