Comparison of Performances of Jaya Algorithm and Cuckoo Search Algorithm Using Benchmark Functions

EasyChair Preprint 5915

Abstract

Nowadays, selecting the best possible solution among several solutions be-comes an important skill for engineering and research. Therefore, engineers are turning to optimization methods as a complementary alternative strategy of exhaustive searching. metaheuristic algorithms have been used successfully for solving different optimization problems. To help engineers select the best meta-heuristic algorithms for their problem, there is a need to evaluate the performance of different meta-heuristic algorithms against each other using common case studies. This paper aims to compare the performance of two meta-heuristic algorithms which are Jaya Algorithm (JA) and Cuckoo Search (CS) using some common benchmark functions. CS and JA have implemented in the same platform (Intellij IDEA Community Edition 2020.2.3) using the same language (Java). The experimental results show better performance than CS in many cases, however in some cases, CS performs better. In term of execution time, CS required less execution time as compared to that of Jaya algorithm.

Keyphrases: Cuckoo Search Algorithm, Jaya algorithm, Optimization, execution time, metaheuristic algorithm

@booklet{EasyChair:5915,
  author    = {Mashuk Ahmed and Abdullah B. Nasser and Kamal Z. Zamli and Sulistyo Heripracoyo},
  title     = {Comparison of Performances of Jaya Algorithm and Cuckoo Search Algorithm Using Benchmark Functions},
  howpublished = {EasyChair Preprint 5915},
  year      = {EasyChair, 2021}}