Title :
Co-Operation of Biology Related Algorithms
Author :
Akhmedova, Shakhnaz ; Semenkin, Eugene
Author_Institution :
Dept. of Syst. Anal. & Oper. Res., Siberian State Aerosp. Univ., Krasnoyarsk, Russia
Abstract :
A new meta-heuristic algorithm, called Co-Operation of Biology Related Algorithms (COBRA), for solving real-parameter optimization problems is introduced and described. The algorithm is based on cooperation of biologically inspired algorithms such as Particle Swarm Optimization (PSO), Wolf Pack Search Algorithm (WPS), Firefly Algorithm (FFA), Cuckoo Search Algorithm (CSA) and Bat Algorithm (BA). The proposed algorithm performance is evaluated on given 28 test functions and its workability and usefulness is demonstrated. Ways of algorithm improvement are discussed.
Keywords :
biology; optimisation; BA; Bat algorithm; COBRA; CSA; Cuckoo search algorithm; FFA; PSO; WPS; Wolf Pack search algorithm; co-operation of biology related algorithm; cooperation of biologically inspired algorithms; firefly algorithm; meta-heuristic algorithm; particle swarm optimization; real-parameter optimization problems; test functions; Algorithm design and analysis; Barium; Birds; Optimization; Sociology; Statistics; cooperation; nature-inspired strategy; real-parameter black box optimization; self-tuning; swarm intelligence;
Conference_Titel :
Evolutionary Computation (CEC), 2013 IEEE Congress on
Conference_Location :
Cancun
Print_ISBN :
978-1-4799-0453-2
Electronic_ISBN :
978-1-4799-0452-5
DOI :
10.1109/CEC.2013.6557831
