DocumentCode :
3724430
Title :
Co-operation of Biology Related Algorithms for Multi-objective Binary Optimization
Author :
Shakhnaz Akhmedova;Eugene Semenkin
Author_Institution :
Dept. of Syst. Anal. &
fYear :
2015
fDate :
7/1/2015 12:00:00 AM
Firstpage :
580
Lastpage :
585
Abstract :
A modification of the self-tuning meta-heuristic, called Co-Operation of Biology Related Algorithms, for multiobjective optimization problems with binary variables (COBRA-bm) is introduced. Its basic idea consists of a cooperative work of five well-known bionic algorithms such as the Particle Swarm Optimization, the Wolf Pack Search, the Firefly Algorithm, the Cuckoo Search Algorithm and the Bat Algorithm, namely their versions for solving optimization problems with binary variables, with the use of Pareto optimality theory. The performance of the mentioned algorithms as well as COBRA-bm on the set of benchmark functions is reported. It was established that the proposed approach COBRA-bm performs either comparably or better than its component bionic algorithms and can be used instead any of them.
Keywords :
"Optimization","Sociology","Statistics","Algorithm design and analysis","Biology","Particle swarm optimization","Search problems"
Publisher :
ieee
Conference_Titel :
Advanced Applied Informatics (IIAI-AAI), 2015 IIAI 4th International Congress on
Print_ISBN :
978-1-4799-9957-6
Type :
conf
DOI :
10.1109/IIAI-AAI.2015.191
Filename :
7373974
Link To Document :
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