A comparative study of population-based optimization algorithms for turning operations

作     者：Yildiz, Ali R. 

作者机构：Bursa Tech Univ Dept Mech Engn Bursa Turkey 

出 版 物：《INFORMATION SCIENCES》 (信息科学)

年 卷 期：2012年第210卷

页      面：81-88页

核心收录：

学科分类：12[管理学] 1201[管理学-管理科学与工程(可授管理学、工学学位)] 08[工学] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

主　　题：Multi-pass turning Differential evolution algorithm Hybrid optimization 

摘      要：In manufacturing industry, turning operations are used to remove unwanted sections of a part to obtain the final product. In this paper a comparison of state-of-the-art optimization techniques to solve multi-pass turning optimization problems is presented. Furthermore, a hybrid technique based on differential evolution algorithm is introduced for solving manufacturing optimization problems. The results have demonstrated the superiority of the hybrid approach over the other techniques like artificial bee colony algorithm, differential evolution algorithm, hybrid particle swarm optimization algorithm, hybrid artificial immune-hill climbing algorithm, hybrid taguchi-harmony search algorithm, hybrid robust genetic algorithm, scatter search algorithm, genetic algorithm and an improved simulated annealing algorithm in terms of convergence speed and efficiency by measuring the number of function evaluations required. (C) 2012 Elsevier Inc. All rights reserved.