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Genetic algorithm with Pareto fronts for multi-criteria optimization case study “milling parameters optimization”

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3 Author(s)
Nafissa Zeghichi ; Labortory of Automatism and manufacturing LAP, Genie Industrial Department, Batna University, Batna 05000, Algeria ; Mekki Assas ; Leila Hayet Mouss

The cutting parameters such as the cutting speed, feed speed, and the chip thickness have huge effects on the machining quality and the productivity rate. The optimal choice of these parameters gives a perfect machining without risks and with high productivity rate. The proposed problem tries to minimizing two nonlinear objectives functions: the machining time and the machining cost under several constraints. The well-chosen of conform optimization methods to resolve this problem gives a quick and reliable decision. The genetic algorithms permit the treatment of non-linear functions. They allow a good exploitation in the field of research as well as the non feasible field is not eliminated but sanctioned with high fitness values and a good exploration by the diversification operations that improve the solution quality.

Published in:

Software, Knowledge Information, Industrial Management and Applications (SKIMA), 2011 5th International Conference on

Date of Conference:

8-11 Sept. 2011