Solution for a Kind of Dynamic Optimization Based on Improved Krill Herd Algorithm

DOI

10.2991/msam-18.2018.32How to use a DOI?

Keywords

dynamic optimization; krill herd algorithm; adaptive cauchy mutation; CVP method; good point sets method; speed factor

Abstract

Considering a kind of dynamic optimization, an improved krill herd (KH) algorithm which is called GSA-KH is proposed in this paper. The improvements consist of three parts: 1) a good point set is constructed to obtain the initial krill population which can promote the representativeness of the initial population; 2) the speed factor is updated according to the changes of the krill population to accelerate the convergence; 3) an adaptive Cauchy mutation is employed so that the algorithm can escape the local optimum reasonably. Simulations on six test functions illustrate that the convergence and accuracy of GSA-KH algorithm are increased greatly than standard KH algorithm. Then the proposed algorithm is applied to solving a dynamic optimization cases.

Copyright

© 2018, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Xingjun Yuan
AU  - Yulei Ge
AU  - Hao Lu
PY  - 2018/07
DA  - 2018/07
TI  - Solution for a Kind of Dynamic Optimization Based on Improved Krill Herd Algorithm
BT  - Proceedings of the 2018 3rd International Conference on Modelling, Simulation and Applied Mathematics (MSAM 2018)
PB  - Atlantis Press
SP  - 146
EP  - 151
SN  - 1951-6851
UR  - https://doi.org/10.2991/msam-18.2018.32
DO  - 10.2991/msam-18.2018.32
ID  - Yuan2018/07
ER  -