DocumentCode
1940656
Title
Initial Version of State Transition Algorithm
Author
Zhou Xiaojun ; Yang Chunhua ; Gui Weihua
Author_Institution
Sch. of Inf. Sci. & Eng., Central South Univ., Changsha, China
fYear
2011
fDate
5-7 Aug. 2011
Firstpage
644
Lastpage
647
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.
Keywords
mathematical operators; optimisation; search problems; STA; benchmark continuous functions; continuous function optimization problems; discrete function optimization problems; expansion operators; general elementary transformation operator; intelligent optimization algorithms; rotation operators; search capability; state transition algorithm; translation operators; Genetic algorithms; Markov processes; Particle swarm optimization; Search problems; Simulated annealing; Traveling salesman problems; State transition algorithm; expansion; general elementary transformation; rotation; translation;
fLanguage
English
Publisher
ieee
Conference_Titel
Digital Manufacturing and Automation (ICDMA), 2011 Second International Conference on
Conference_Location
Zhangjiajie, Hunan
Print_ISBN
978-1-4577-0755-1
Electronic_ISBN
978-0-7695-4455-7
Type
conf
DOI
10.1109/ICDMA.2011.160
Filename
6051929
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