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A novel algorithm for efficient utilization of gemstone using genetic algorithm

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Abstract

In this paper, a novel method is used for fitting a polished and faceted object which is also called as a gem or diamond in a given rough gemstone using genetic algorithm. The goal of proposed Genetic Algorithm based Multiple Object Fitting algorithm is to maximize the utilization of the volume of rough gemstone by fitting the largest number of polished gemstones inside rough gemstone. One of the most difficult tasks is to fit the number of polished gemstones and positioning of each and every polished gemstone within the rough gemstone in order to minimize the waste. This is an optimization problem that is used to find the position, orientation, and scaling parameters of all the polished gemstones within a given rough gemstone such that the sum of volumes of all polished gemstones is maximized. The major novelty of proposed work is to fit more than one object in a given rough stone. The simulation results demonstrate the efficiency of our proposed algorithm.

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References

  1. Cartier LE (2019) Gemstones and sustainable development: perspectives and trends in mining, processing and trade of precious stones. Extr Ind Soc 6(4):1013–1016

    Google Scholar 

  2. Ceulemans T (2007) Device and kit for visualizing a cutting regime of a diamond, and a method for determining a cutting regime. US Patent US20070186918 A1, 16 Aug 2007

  3. da Silva V, Ritt M, da Paz Carvalho J, Brusso M, da Silva J, Zanatta A (2012) A real-valued genetic algorithm for gemstone cutting. In: XXXVIII Conferencia Latinoamericana En, Informatica (CLEI), Medellin, 2012

  4. Winterfeld A (2008) Application of general semi-infinite programming to lapidary cutting problems. Eur J Oper Res 191(3):838–854

    Article  MathSciNet  Google Scholar 

  5. Nguyen VH, Strodiot J-J (1992) Computing a global optimal solution to a design centering problem. Math Program 53(1–3):111–123

    Article  MathSciNet  Google Scholar 

  6. Stein O (2006) A semi-infinite approach to design centering. In: Dempe S, Kalashnikov V (eds) Optimization with multivalued mappings, Springer optimization and its applications. Springer, Berlin, pp 209–228

    Chapter  Google Scholar 

  7. Viswambharan A (1988) Optimisation in diamond cutting. Technical report, University of Auckland, New Zealand

  8. Fiorest MB, Brusso MJ (2012) Algoritmos Genéticos Na Otimização Da Lapidação De Gemas Coradas. Revista CIATEC-UPF 3(2):44–55

    Google Scholar 

  9. Mitchell M (1999) An introduction to genetic algorithms. MIT Press, Cambridge

    MATH  Google Scholar 

  10. Lambora A, Gupta K, Chopra K (2019) Genetic algorithm: a literature review. In: 2019 international conference on machine learning, big data, cloud and parallel computing (COMITCon). IEEE, pp 380–384

  11. Haldurai L, Madhubala T, Rajalakshmi R (2016) A study on genetic algorithm and its applications. Int J Comput Sci Eng 4(10):2347–2693

    Google Scholar 

  12. Mol AA, Martins-Filho LS, da Silva JDS, Rocha R (2007) Efficiency parameters estimation in gemstones cut design using artificial neural networks. Comput Mater Sci 38(4):727–736

    Article  Google Scholar 

  13. 3D Gemas Repository [Online]. http://usuarios.upf.br/~3dgemas/repositorio/index.php. Accessed 06 Dec 2013

  14. Garland M (2004) Mixkit: QSlim simplification software [Online]. http://mgarland.org/software/qslim.html. Accessed 01 Dec 2019

  15. Wall M (2019) GAlib: a C ++ library of genetic algorithm components [Online]. http://lancet.mit.edu/ga/. Accessed 01 Dec 2019

  16. Sunday D (2019) Intersections of rays, segments, planes [Online]. http://geomalgorithms.com/a06-_intersect-2.html. Accessed 06 Dec 2019

  17. OpenGL: the industry’s foundation for high performance graphics [Online]. http://www.opengl.org/. Accessed 06 Dec 2019

Download references

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Authors and Affiliations

  1. U. V. Patel College of Engineering, Mehsana, Gujarat, India

    Hiten M. Sadani

  2. Government Engineering College, Gandhinagar, Gujarat, India

    Nikhil Kumar Singh

  3. Dhirubhai Ambani Institute of Information and Communication Technology (DA-IICT), Gandhinagar, Gujarat, India

    Manish Khare

Authors
  1. Hiten M. Sadani
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  2. Nikhil Kumar Singh
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  3. Manish Khare
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Correspondence to Manish Khare.

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Sadani, H.M., Singh, N.K. & Khare, M. A novel algorithm for efficient utilization of gemstone using genetic algorithm. Evol. Intel. 14, 1065–1073 (2021). https://doi.org/10.1007/s12065-020-00542-1

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  • DOI: https://doi.org/10.1007/s12065-020-00542-1

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