Multi-Objective Optimization Using Genetic Algorithms of Multi-Pass Turning Process
Abstract: In this paper we present a multi-optimization technique based on genetic algorithms to search optimal cuttings parameters such as cutting depth, feed rate and cutting speed of multi-pass turning processes. Tow objective functions are simultaneously optimized under a set of practical of machining constraints, the first objective function is cutting cost and the second one is the used tool life time. The proposed model deals multi-pass turning processes where the cutting operations are divided into multi-pass rough machining and finish machining. Results obtained from Genetic Algorithms method are presented in Pareto frontier graphic; this technique helps us in decision making process. An example is presented to illustrate the procedure of this technique.
Cite this paper: A. Jabri, A. Barkany and A. Khalfi, "Multi-Objective Optimization Using Genetic Algorithms of Multi-Pass Turning Process," Engineering, Vol. 5 No. 7, 2013, pp. 601-610. doi: 10.4236/eng.2013.57072.
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