Abstract
This paper proposes the optimization process using real coded genetic algorithm for selecting optimal conditions in multi-pass turning operations for Computer Numerically controlled (CNC) Machining tools. The cutting processes comprise multi-pass rough machining and finish machining with several constraints around 20, imposed during roughing and finishing operations on tool life, surface finish, cutting forces, machining power and chip–tool interface. In this paper, a Real Coded Genetic Algorithm namely Laplace Crossover Power Mutation GA is employed to obtain the optimal set of parameters that minimize the total unit production cost under several constraints. For handling Constraints parameter less approach is used. Results obtained using LXPM-GA are compared with the results obtained using PSO, GA and ACO as recorded in literature.
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Chauhan, P. (2021). Real Coded Genetic Algorithm for Selecting Optimal Machining Conditions. In: Singh, D., Awasthi, A.K., Zelinka, I., Deep, K. (eds) Proceedings of International Conference on Scientific and Natural Computing. Algorithms for Intelligent Systems. Springer, Singapore. https://doi.org/10.1007/978-981-16-1528-3_8
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DOI: https://doi.org/10.1007/978-981-16-1528-3_8
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