Title :
Study of parametric optimization of the Cuckoo Search algorithm
Author :
Mallick, Arijit ; Roy, Sandip ; Chaudhuri, Sheli Sinha ; Roy, Sandip
Author_Institution :
Dept. of Electron. & Instrum. Eng., Jadavpur Univ., Kolkata, India
fDate :
Jan. 31 2014-Feb. 2 2014
Abstract :
Cuckoo search (CS) is one of the latest and most efficient optimization techniques developed so far. Several attempts have been made in past in order to improve the efficiency of CS algorithm. In this paper we have tried to exploit several parameters of the CS algorithm in order to increase its efficiency. Cuckoo search is a metaheuristic optimization technique. Its parameters involve the Levy distribution factor beta (β) and the probability factor (P) with which solutions are replaced with new solutions. Hence for optimum values of the aforesaid parameters, efficiency of CS algorithm can be improved and can be used to solve optimization problems.
Keywords :
evolutionary computation; search problems; statistical distributions; CS algorithm; Levy distribution factor beta; cuckoo search algorithm; metaheuristic optimization technique; parametric optimization; probability factor; Algorithm design and analysis; Birds; Convergence; Genetic algorithms; Instruments; Optimization; Particle swarm optimization; Cuckoo search; Levy distribution; metaheuristic; optimization;
Conference_Titel :
Control, Instrumentation, Energy and Communication (CIEC), 2014 International Conference on
Conference_Location :
Calcutta
DOI :
10.1109/CIEC.2014.6959194
