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A hybrid cuckoo search algorithm with Nelder Mead method for solving global optimization problems.

Ali AF, Tawhid MA - Springerplus (2016)

Bottom Line: Cuckoo search algorithm is a promising metaheuristic population based method.It has been applied to solve many real life problems.We call the proposed algorithm by hybrid cuckoo search and Nelder-Mead method (HCSNM).

View Article: PubMed Central - PubMed

Affiliation: Department of Computer Science, Faculty of Computers and Informatics, Suez Canal University, Ismailia, Egypt ; Department of Mathematics and Statistics, Faculty of Science, Thompson Rivers University, 900 McGill Road, Kamloop, BC V2C 0C8 Canada.

ABSTRACT
Cuckoo search algorithm is a promising metaheuristic population based method. It has been applied to solve many real life problems. In this paper, we propose a new cuckoo search algorithm by combining the cuckoo search algorithm with the Nelder-Mead method in order to solve the integer and minimax optimization problems. We call the proposed algorithm by hybrid cuckoo search and Nelder-Mead method (HCSNM). HCSNM starts the search by applying the standard cuckoo search for number of iterations then the best obtained solution is passing to the Nelder-Mead algorithm as an intensification process in order to accelerate the search and overcome the slow convergence of the standard cuckoo search algorithm. The proposed algorithm is balancing between the global exploration of the Cuckoo search algorithm and the deep exploitation of the Nelder-Mead method. We test HCSNM algorithm on seven integer programming problems and ten minimax problems and compare against eight algorithms for solving integer programming problems and seven algorithms for solving minimax problems. The experiments results show the efficiency of the proposed algorithm and its ability to solve integer and minimax optimization problems in reasonable time.

No MeSH data available.


The effects of the number of population size
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Fig1: The effects of the number of population size

Mentions: Population size n The experimental tests show that the best population size is , we applied the proposed algorithm with different population size in order to test the efficiency of the selected population size number. FigureĀ 1 shows that the best population size is while increasing this number to will increase the function evaluation without a big improvement in the function values.


A hybrid cuckoo search algorithm with Nelder Mead method for solving global optimization problems.

Ali AF, Tawhid MA - Springerplus (2016)

The effects of the number of population size
© Copyright Policy - OpenAccess
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4835425&req=5

Fig1: The effects of the number of population size
Mentions: Population size n The experimental tests show that the best population size is , we applied the proposed algorithm with different population size in order to test the efficiency of the selected population size number. FigureĀ 1 shows that the best population size is while increasing this number to will increase the function evaluation without a big improvement in the function values.

Bottom Line: Cuckoo search algorithm is a promising metaheuristic population based method.It has been applied to solve many real life problems.We call the proposed algorithm by hybrid cuckoo search and Nelder-Mead method (HCSNM).

View Article: PubMed Central - PubMed

Affiliation: Department of Computer Science, Faculty of Computers and Informatics, Suez Canal University, Ismailia, Egypt ; Department of Mathematics and Statistics, Faculty of Science, Thompson Rivers University, 900 McGill Road, Kamloop, BC V2C 0C8 Canada.

ABSTRACT
Cuckoo search algorithm is a promising metaheuristic population based method. It has been applied to solve many real life problems. In this paper, we propose a new cuckoo search algorithm by combining the cuckoo search algorithm with the Nelder-Mead method in order to solve the integer and minimax optimization problems. We call the proposed algorithm by hybrid cuckoo search and Nelder-Mead method (HCSNM). HCSNM starts the search by applying the standard cuckoo search for number of iterations then the best obtained solution is passing to the Nelder-Mead algorithm as an intensification process in order to accelerate the search and overcome the slow convergence of the standard cuckoo search algorithm. The proposed algorithm is balancing between the global exploration of the Cuckoo search algorithm and the deep exploitation of the Nelder-Mead method. We test HCSNM algorithm on seven integer programming problems and ten minimax problems and compare against eight algorithms for solving integer programming problems and seven algorithms for solving minimax problems. The experiments results show the efficiency of the proposed algorithm and its ability to solve integer and minimax optimization problems in reasonable time.

No MeSH data available.