Initial Version of State Transition Algorithm
Optimization and Control
2012-10-15 v2 Neural and Evolutionary Computing
Abstract
In terms of the concepts of state and state transition, a new algorithm-State Transition Algorithm (STA) is proposed in order to probe into classical and intelligent optimization algorithms. On the basis of state and state transition, it becomes much simpler and easier to understand. As for continuous function optimization problems, three special operators named rotation, translation and expansion are presented. While for discrete function optimization problems, an operator called general elementary transformation is introduced. Finally, with 4 common benchmark continuous functions and a discrete problem used to test the performance of STA, the experiment shows that STA is a promising algorithm due to its good search capability.
Cite
@article{arxiv.1208.0228,
title = {Initial Version of State Transition Algorithm},
author = {Xiaojun Zhou and Chunhua Yang and Weihua Gui},
journal= {arXiv preprint arXiv:1208.0228},
year = {2012}
}