Please use this identifier to cite or link to this item: https://doi.org/10.1007/s00170-003-1789-5
Title: Optimisation of multi-pass milling using genetic algorithm and genetic simulated annealing
Authors: Wang, Z.G. 
Wong, Y.S. 
Rahman, M. 
Keywords: Genetic algorithm
Genetic simulated annealing
Milling
Issue Date: Nov-2004
Source: Wang, Z.G., Wong, Y.S., Rahman, M. (2004-11). Optimisation of multi-pass milling using genetic algorithm and genetic simulated annealing. International Journal of Advanced Manufacturing Technology 24 (9-10) : 727-732. ScholarBank@NUS Repository. https://doi.org/10.1007/s00170-003-1789-5
Abstract: The selection of optimal machining parameters plays an important part in computer-aided manufacturing. The optimisation of machining parameters is still the subject of many studies. Genetic algorithm (GA) and simulated annealing (SA) have been applied to many difficult combinatorial optimisation problems with certain strengths and weaknesses. In this paper, genetic simulated annealing (GSA), which is a hybrid of GA and SA, is used to determine optimal machining parameters for milling operations. For comparison, basic GA is also chosen as another optimisation method. An application example that has previously been solved using geometric programming (GP) method is presented. The results indicate that GSA is more efficient than GA and GP in the application of optimisation.
Source Title: International Journal of Advanced Manufacturing Technology
URI: http://scholarbank.nus.edu.sg/handle/10635/61017
ISSN: 02683768
DOI: 10.1007/s00170-003-1789-5
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