A comparative study of population-based optimization algorithms for turning operations
► This paper presents a hybrid optimization method based on differential evolution algorithm. ► The hybrid approach (DERE) is used to select optimal machining parameters in turning operations. ► The DERE outperforms all the compared algorithms in solving the turning optimization problems. In manufac...
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| Published in | Information sciences Vol. 210; pp. 81 - 88 |
|---|---|
| Main Author | |
| Format | Journal Article |
| Language | English |
| Published |
Elsevier Inc
25.11.2012
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| Subjects | |
| Online Access | Get full text |
| ISSN | 0020-0255 1872-6291 |
| DOI | 10.1016/j.ins.2012.03.005 |
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| Abstract | ► This paper presents a hybrid optimization method based on differential evolution algorithm. ► The hybrid approach (DERE) is used to select optimal machining parameters in turning operations. ► The DERE outperforms all the compared algorithms in solving the turning optimization problems.
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. |
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| AbstractList | ► This paper presents a hybrid optimization method based on differential evolution algorithm. ► The hybrid approach (DERE) is used to select optimal machining parameters in turning operations. ► The DERE outperforms all the compared algorithms in solving the turning optimization problems.
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. 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. |
| Author | Yildiz, Ali R. |
| Author_xml | – sequence: 1 givenname: Ali R. surname: Yildiz fullname: Yildiz, Ali R. email: aliriza.yildiz@btu.edu.tr organization: Bursa Technical University, Department of Mechanical Engineering, Bursa, Turkey |
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| Snippet | ► This paper presents a hybrid optimization method based on differential evolution algorithm. ► The hybrid approach (DERE) is used to select optimal machining... 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... |
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| SubjectTerms | Algorithms Convergence Differential evolution algorithm Evolution Genetic algorithms Hybrid optimization Multi-pass turning Optimization Search algorithms Simulated annealing Turning |
| Title | A comparative study of population-based optimization algorithms for turning operations |
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