A new hybrid artificial bee colony algorithm for robust optimal design and manufacturing - Yildiz, Ali R. (Applied soft computing, 2013)
[Display omitted] ► A new optimization method (HRABC) based on artificial bee colony algorithm and Taguchi is developed. ► The HRABC is applied to the design and manufacturing optimization problems. ► The HRABC gives an effective way to find global optimum solutions for real-world optimization problems. The purpose of this paper is to develop a novel hybrid optimization method (HRABC) based on artificial bee colony algorithm and Taguchi method. The proposed approach is applied to a structural design optimization of a vehicle component and a multi-tool milling optimization problem. A comparison of state-of-the-art optimization techniques for the design and manufacturing optimization problems is presented. The results have demonstrated the superiority of the HRABC over the other techniques like differential evolution algorithm, harmony search algorithm, particle swarm optimization algorithm, artificial immune algorithm, ant colony algorithm, hybrid robust genetic algorithm, scatter search algorithm, genetic algorithm in terms of convergence speed and efficiency by measuring the number of function evaluations required.