A Collection of Contemporary Research Articles in Electronics, Communication & Computation- Book ISBN- 978-81-948050-7-6

Authors: Himansu Bhushan Mohapatra, Mrutyunjay Rout

Abstract: 

Metaheuristic modern optimization techniques are Superior to the traditional optimization techniques to find the global optimization solution. These techniques are verified as efficient for optimization in almost all fields, but still, they have some restrictions in one or another feature. Due to this, more and more research is required to check the algorithms for different problems to verify their suitability for the numerical problem. In this paper, performances of Teaching-Learning-based optimization, Artificial Bee Colony and Differential Evolution algorithms were compared on general benchmark problems. The effect of problem dimensional and control parameters on the performance of the algorithms was verified, and the algorithms were measured in terms of mean, the standard deviation of the fitness function values.

Keywords: Meta-heuristic optimization, teaching-Learning- Based Optimization, Artificial Bee Colony Optimization, Differential Evolution and Benchmark functions