A Novel Hybrid Gazelle Optimization Algorithm with Differential Evolution for Solving Engineering Design Problem

This paper introduces a novel hybrid optimization algorithm that combines the Gazelle Optimization Algorithm (GOA) with Differential Evolution (DE) to enhance performance in optimizing engineering design problems. The suggested hybrid GOA-DE algorithm takes advantage of the best parts of both schemes by adding DE's mutation and crossover operations to GOA's iterative process. This integration aims to improve both the exploration and exploitation capabilities of the algorithm. The hybrid GOA-DE algorithm was tested on various engineering design problems to assess its performance compared to traditional GOA and DE algorithms. Experimental results indicate that the hybrid GOA-DE algorithm exhibits superior convergence speed and accuracy in identifying optimal solutions. By incorporating DE's mechanisms, the algorithm achieves a more robust search process, effectively balancing exploration and exploitation, leading to improved optimization outcomes.