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Reseach Article

Parameter optimization of Cuckoo Search Algorithm for Multi Dimensional Function Optimization Problem

by Mohammad Shafiul Alam, Samiha Sara Prima, Sanonda Datta Gupta, Jannatun Razia
Communications on Applied Electronics
Foundation of Computer Science (FCS), NY, USA
Volume 7 - Number 18
Year of Publication: 2018
Authors: Mohammad Shafiul Alam, Samiha Sara Prima, Sanonda Datta Gupta, Jannatun Razia
10.5120/cae2018652776

Mohammad Shafiul Alam, Samiha Sara Prima, Sanonda Datta Gupta, Jannatun Razia . Parameter optimization of Cuckoo Search Algorithm for Multi Dimensional Function Optimization Problem. Communications on Applied Electronics. 7, 18 ( Jul 2018), 6-10. DOI=10.5120/cae2018652776

@article{ 10.5120/cae2018652776,
author = { Mohammad Shafiul Alam, Samiha Sara Prima, Sanonda Datta Gupta, Jannatun Razia },
title = { Parameter optimization of Cuckoo Search Algorithm for Multi Dimensional Function Optimization Problem },
journal = { Communications on Applied Electronics },
issue_date = { Jul 2018 },
volume = { 7 },
number = { 18 },
month = { Jul },
year = { 2018 },
issn = { 2394-4714 },
pages = { 6-10 },
numpages = {9},
url = { https://www.caeaccess.org/archives/volume7/number18/821-2018652776/ },
doi = { 10.5120/cae2018652776 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2023-09-04T20:02:11.301550+05:30
%A Mohammad Shafiul Alam
%A Samiha Sara Prima
%A Sanonda Datta Gupta
%A Jannatun Razia
%T Parameter optimization of Cuckoo Search Algorithm for Multi Dimensional Function Optimization Problem
%J Communications on Applied Electronics
%@ 2394-4714
%V 7
%N 18
%P 6-10
%D 2018
%I Foundation of Computer Science (FCS), NY, USA
Abstract

The Cuckoo Search Algorithm is a recently developed nature inspired meta heuristic algorithm, which is established on the breeding behavior of Cuckoo species. Cuckoo search can be applied on a large variety of optimization problems. The main advantage of this search algorithm is its simplicity and better performance than many other agent or population based meta heuristic algorithms. The algorithm uses only one controlling parameter p, which makes it easier to implement and control. This parameter p, combined with the random walk mutations implemented by Lévy Flights, can control the performance and degree of exploration and exploitation of the algorithm. In this paper we have conducted a few experiments on Cuckoo Search algorithm with Lévy flights to discover the necessary conditions needed for the better performance of the algorithm. For this purpose we have taken different values of the controlling parameter p and observed the performance of the algorithm on benchmark problems, as well as its exploration and exploitation characteristics over different groups of benchmark functions.

References
  1. X. Yang and S. Deb, "Cuckoo search: recent advances and applications", Neural Computing and Applications, vol. 24, no. 1, pp. 169-174, 2013.
  2. Y. Xu, P. Fan and L. Yuan, "A Simple and Efficient Artificial Bee Colony Algorithm", Mathematical Problems in Engineering, vol. 2013, pp. 1-9, 2013.
  3. X. Yang and X. He, "Bat algorithm: literature review and applications", International Journal of Bio-Inspired Computation, vol. 5, no. 3, p. 141, 2013.
  4. X. Yang, "Flower Pollination Algorithm for Global Optimization", Unconventional Computation and Natural Computation, pp. 240-249, 2012.
  5. X. Yang, M. Karamanoglu and X. He, "Multi-objective Flower Algorithm for Optimization", Procedia Computer Science, vol. 18, pp. 861-868, 2013.
  6. M. Abdel-Baset and I. Hezam, "A Hybrid Flower Pollination Algorithm for Engineering Optimization Problems", International Journal of Computer Applications, vol. 140, no. 12, pp. 10-23, 2016.
  7. O. Raouf, M. Baset and I. henawy, "A New Hybrid Flower Pollination Algorithm for Solving Constrained Global Optimization Problems", 2014.
  8. O. Abdel Raouf, I. El henawy and M. Abdel Baset, "A Novel Hybrid Flower Pollination Algorithm with Chaotic Harmony Search for Solving Sudoku Puzzles", International Journal of Modern Education and Computer Science, vol. 6, no. 3, pp. 38-44, 2014.
  9. B. Nozohour-leilabady and B. Fazelabdolabadi, "On the application of artificial bee colony (ABC) algorithm for optimization of well placements in fractured reservoirs; efficiency comparison with the particle swarm optimization (PSO) methodology", Petroleum, vol. 2, no. 1, pp. 79-89, 2016.
  10. P. N. Suganthan, N. Hansen, J. J. Liang, K. Deb, Y.-P. Chen and A. Auger, "Problem Definitions and Evaluation Criteria for the CEC 2005 Special Session on Real-Parameter Opt.mization", Technical Report, Nanyang Technological University (NTU), Singapore, May 2005 And KanGAL Report #2005005, IIT Kanpur, India.
  11. B. Liu, Q. Chen and Q. Zhang, J. J. Liang, P. N. Suganthan, "Problem Definitions and Evaluation Criteria for Computationally Expensive Single Objective Numerical Optimization", Technical Report, Zhengzhou University, China and Technical Report, NTU, Singapore, December 2013.
Index Terms

Computer Science
Information Sciences

Keywords

Cuckoo search algorithm function optimization Lévy flights mutation parameter optimization.