AN EFFICIENT MODIFIED CUCKOO SEARCH OPTIMIZATION WITH THE RATIONAL BARRIER FUNCTION
Journal Title: International Journal of Mathematics and Computer Applications Research (IJMCAR) - Year 2018, Vol 8, Issue 5
Abstract
Recent modern optimization algorithms are often very successful in solving NP-hard improvement problems. One of the main disadvantages of the search algorithm in cuckoo (CS) is the weakness of its ability as a local search algorithm and slow in its speed of convergence, which results in a limited access to the target. There are two categories that can be solved by this algorithm: First, the unconstrained functions are solved. Second, which is the focus of this article, is the constraint functions and how to deal with them using a rational formula of the Barrier function. The results show that the CRB (Cuckoo & Rational Barrier Function) algorithm has a better convergence velocity than the algorithm (CS) by observing the separation of the numerical results of the browser in which the accuracy of the new algorithm on some engineering functions.
Authors and Affiliations
RANA Z Al-KAWAZ, HUDA I AHMED, ABBAS Y Al-BAYATI
Keywords
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- EP ID EP430378
- DOI 10.24247/ijmcaroct20182
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AN EFFICIENT MODIFIED CUCKOO SEARCH OPTIMIZATION WITH THE RATIONAL BARRIER FUNCTION
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