On the problem of solving the optimization for continuous space based on information distribution function of ant colony algorithm

3rd International Conference on Advances in Energy, Environment and Chemical Engineering

能源学;生态环境科学;化学工业

Min, Huang^1 ; Na, Cai^1

Marine Information Engineering Institute, Hainan Tropical Marine Institute, Sanya, Hainan

572022, China^1

关键词: Amount of information;    Ant colony algorithms;    Continuous space optimization;    Convergence performance;    Convergence rates;    Improved ant colony algorithm;    Information distributions;    Number of iterations;   

Others  :  https://iopscience.iop.org/article/10.1088/1755-1315/69/1/012121/pdf
DOI  :  10.1088/1755-1315/69/1/012121

学科分类：环境科学（综合）

来源: IOP

【 摘 要 】

These years, ant colony algorithm has been widely used in solving the domain of discrete space optimization, while the research on solving the continuous space optimization was relatively little. Based on the original optimization for continuous space, the article proposes the improved ant colony algorithm which is used to Solve the optimization for continuous space, so as to overcome the ant colony algorithm's disadvantages of searching for a long time in continuous space. The article improves the solving way for the total amount of information of each interval and the due number of ants. The article also introduces a function of changes with the increase of the number of iterations in order to enhance the convergence rate of the improved ant colony algorithm. The simulation results show that compared with the result in literature[5], the suggested improved ant colony algorithm that based on the information distribution function has a better convergence performance. Thus, the article provides a new feasible and effective method for ant colony algorithm to solve this kind of problem.