Title :
Natural Inspired Computational Intelligence Method: Saplings Growing up Algorithm
Author_Institution :
Firat Univ., Elazg
Abstract :
In this paper, we proposed a new computational method inspired by the cultivating and growing up saplings (trees). Sowing saplings in the nature consists of two steps: Sowing saplings, growing up of saplings (branching, mating, and vaccinating). We inspired by this natural process and developed a computational method which is called sowing and growing up of samplings optimization - saplings growing up algorithm (SGuA). This method contains two phases: sowing phase and growing up phase. The mating operator is a global search operator by exchanging information in the two saplings. Branching operator is a local search operator by changing the branches of a sapling probabilistically. Vaccinating operator is a search operator by using dissimilar saplings. After application of the proposed method to benchmark functions, we observed that this method is superior to genetic algorithms in case of finding better solutions and number of function evaluations.
Keywords :
artificial intelligence; genetic algorithms; branching operator; genetic algorithms; growing up phase; mating operator; natural inspired computational intelligence method; optimization; saplings growing up algorithm; search operator; sowing phase; vaccinating operator; Artificial intelligence; Computational intelligence; Computational modeling; Evolutionary computation; Genetic algorithms; Genetic programming; Optimization methods; Robot programming; Sampling methods; Upper bound;
Conference_Titel :
Computational Cybernetics, 2007. ICCC 2007. IEEE International Conference on
Conference_Location :
Gammarth
Print_ISBN :
978-1-4244-1146-7
Electronic_ISBN :
978-1-4244-1146-7
DOI :
10.1109/ICCCYB.2007.4402038