A  Hybrid Bird Mating Optimizer for Welded Beam Design Optimization Problem: Design Optimization

Ali Hikmat Ibrahem; Adnan Mohsin Abdulazeez

doi:10.33022/ijcs.v13i1.3721

Authors

Ali Hikmat Ibrahem Information Technology Department, Technical College of Informatics-Akre, Akre University for Applied Sceiences, Duhok, Kurdistan Region of Iraq
Adnan Mohsin Abdulazeez Energy Engineering Department, Technical college of Engineering-Duhok, Duhok Polytechnic University, Duhok 42001, Kurdistan Region, Iraq

DOI:

https://doi.org/10.33022/ijcs.v13i1.3721

Keywords:

Bird Mating Optimizer, A Hybrid Bird Mating Optimizer, Differential Evolution, Penalty Function.

Abstract

This study introduces a hybridization of the Bird Mating Optimizer (BMO) with Differential Evolution (DE). The Bird Mating Optimizer exhibits certain limitations, such as a slow convergence rate and a tendency to become trapped in local optima. To address these issues, a new method, BMO-DE, is proposed to enhance the performance of the BMO swarm intelligence algorithm. BMO-DE is a versatile swarm intelligence algorithm applicable to various engineering problems. In this research, it is specifically employed in the optimization of welded beam design, a type of problem characterized by numerous constraints. The penalty function approach is used to handle the constraints associated with welded beam design. Comparative analysis indicates that the proposed BMO-DE method outperforms other swarm intelligence algorithms in tackling this category of problems. Notably, the method demonstrates efficacy in finding optimal solutions with a low number of objective function evaluations, making it a potent and promising approach for addressing such problems.