Please use this identifier to cite or link to this item: http://hdl.handle.net/11452/21506
Title: Hybrid enhanced genetic algorithm to select optimal machining parameters in turning operation
Authors: Uludağ Üniversitesi/Mühendislik Fakültesi/Makine Mühendisliği Bölümü.
0000-0003-1790-6987
Yıldız, Ali Rıza
Öztürk, Ferruh
AAG-9923-2021
F-7426-2011
7102365439
56271685800
Keywords: Engineering
Robust parameter design
Genetic algorithm
Turning optimization
Optimization
Design
Computational methods
Constraint theory
Machining
Optimal control systems
Optimization
Problem solving
Single objective optimization problems
Issue Date: 2006
Publisher: Sage Publications
Citation: Yıldız, A. R. ve Öztürk, F. (2006). ''Hybrid enhanced genetic algorithm to select optimal machining parameters in turning operation''. Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture, 220(12), 2041-2053.
Abstract: The current paper presents a hybrid enhanced genetic algorithm that is developed for solving the optimization problems in design and manufacturing. The present approach is applied to optimize turning operation for the determination of cutting parameters considering minimum production cost under a set of machining constraints. A refined design space for population is introduced by integrating the robust parameter design concept into the genetic algorithm to solve multi-objective and single-objective optimization problems. First, the proposed approach is validated using test problems and metrics taken from literature. Finally, it is applied to the turning optimization problem. The computational experimental results show the effectiveness of the proposed approach in the turning optimization problem.
URI: https://doi.org/10.1243/09544054JEM570
https://journals.sagepub.com/doi/10.1243/09544054JEM570
http://hdl.handle.net/11452/21506
ISSN: 0954-4054
2041-2975
Appears in Collections:Scopus
Web of Science

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