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Optimisation of multi-pass milling using genetic algorithm and genetic simulated annealing

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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.

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Authors and Affiliations

  1. Department of Mechanical and Production Engineering, National University of Singapore, 10 Kent Ridge Crescent, Singapore, 119260

    Z.G. Wang, Y.S. Wong & M. Rahman

Authors
  1. Z.G. Wang
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  2. Y.S. Wong
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  3. M. Rahman
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Correspondence to Y.S. Wong.

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Wang, Z., Wong, Y. & Rahman, M. Optimisation of multi-pass milling using genetic algorithm and genetic simulated annealing. Int J Adv Manuf Technol 24, 727–732 (2004). https://doi.org/10.1007/s00170-003-1789-5

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  • DOI: https://doi.org/10.1007/s00170-003-1789-5

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