GREY WOLF OPTIMIZATION METHOD ENHANCED WITH CLUSTERING TECHNIQUE FOR SOLVING NONLINEAR EQUATION SYSTEMS AND SEVERAL ENGINEERING PROBLEMS

• Main Author: Rasya Septiandi, Rivaldi
• Format: Final Project
• Language: Indonesia
• Online Access: https://digilib.itb.ac.id/gdl/view/78058
• Institution: Institut Teknologi Bandung

Metaheuristic methods have been widely used to solve various optimization problems. One of these metaheuristic methods is Grey Wolf Optimization, first proposed by Mirjalili in 2014. This method draws inspiration from social hierarchies and the hunting mechanism of gray wolves (Mirjalili dkk., 2014). In this final project, the author will improvise upon this method to make it applicable for solving non-linear equation systems, Diophantine equations and systems, multimodal functions, and several real problems in the field of engineering. The author will also integrate the GWO method with clustering techniques to divide a domain based on regions that are believed to contain optimal solutions (Sidarto and Kania, 2015). The Sobol sequence is employed to generate the initial population, ensuring a more uniform distribution of initial values. Experimental results demonstrate that the GWO algorithm yields favorable outcomes in searching for optimal values and exhibits a sufficiently fast convergence rate.