DocumentCode :
1580624
Title :
Symbiotic Tabu Search, A General Evolutionary Optimization Approach
Author :
Halavati, Ramin ; Shouraki, Saeed Bagheri ; Jashmi, Bahareh Jafari ; Heravi, Mojdeh Jalali
Author_Institution :
Sharif Univ. of Technol., Tehran
fYear :
2007
Firstpage :
138
Lastpage :
143
Abstract :
Recombination in the Genetic Algorithm (GA) is supposed to extract the component characteristics from two parents and reassemble them in different combinations - hopefully producing an offspring that has the good characteristics of both parents. Symbiotic Combination is formerly introduced as an alternative for sexual recombination operator to overcome the need of explicit design of recombination operators in GA. This paper presents an optimization algorithm based on using this operator in Tabu Search. The algorithm is benchmarked on two problem sets and is compared with standard genetic algorithm and symbiotic evolutionary adaptation model, showing success rates higher than both cited algorithms.
Keywords :
genetic algorithms; search problems; evolutionary optimization approach; genetic algorithm; recombination operators; sexual recombination operator; symbiotic Tabu Search; symbiotic combination; symbiotic evolutionary adaptation model; Adaptation model; Bioinformatics; Biological cells; Couplings; Genetic algorithms; Genetic engineering; Genomics; Hybrid intelligent systems; Organisms; Symbiosis;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Hybrid Intelligent Systems, 2007. HIS 2007. 7th International Conference on
Conference_Location :
Kaiserlautern
Print_ISBN :
978-0-7695-2946-2
Type :
conf
DOI :
10.1109/HIS.2007.70
Filename :
4344041
Link To Document :
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