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NetLogo Teaching Tool to Illustrate the Cooling Process in Simulated Annealing Using the Metropolis Model

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Industry 4.0: The Power of Data

Abstract

Simulated annealing is one of the most popular metaheuristic optimization techniques used in engineering and management to solve combinatorial problems. The algorithm is inspired by the thermodynamic process that occurs in the annealing treatment in metallurgy. Although it is simple to implement, its general operating mechanism and the rationale behind the search strategy are not always that intuitive. In this work, we present a teaching tool implemented in NetLogo that illustrates the metaphor of both processes and the effect of annealing cooling schedules on the quality of the solutions obtained.

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References

  1. Bautista-Valhondo J (2020) Metaheurísticas en Ingeniería. Dextra

    Google Scholar 

  2. Zäpfel G, Braune R, Bögl M (2010) Metaheuristic Search Concepts. Springer Berlin Heidelberg. https://doi.org/10.1007/978-3-642-11343-7

  3. Sörensen K, Glover FW (2013) Metaheuristics. In: Encyclopedia of operations research and management science. Springer US, Boston, MA, pp 960–970. https://doi.org/10.1007/978-1-4419-1153-7_1167.

  4. Talbi EG (2009) Metaheuristics: from design to implementation. Wiley, Hoboken, NJ

    Book  MATH  Google Scholar 

  5. Kirkpatrick S, Gelatt CD, Vecchi MP (1983) Optimization by simulated annealing. Science 80(220):671–680. https://doi.org/10.1126/science.220.4598.671

  6. Metropolis N, Rosenbluth AW, Rosenbluth MN, Teller AH, Teller E (1953) Equation of state calculations by fast computing machines. J Chem Phys 21:1087–1092. https://doi.org/10.1063/1.1699114

    Article  MATH  Google Scholar 

  7. Wilensky U (1999) NetLogo. Center for connected learning and computer-based modeling, Northwestern University, Evanston, IL

    Google Scholar 

  8. Stonedahl F, Wilensky U (2009) NetLogo simulated annealing model. Center for connected learning and computer-based modeling, Northwestern University, Evanston, IL

    Google Scholar 

  9. Geman S, Geman D (1984) Stochastic relaxation, gibbs distributions, and the Bayesian restoration of images. IEEE Trans Pattern Anal Mach Intell PAMI-6, 721–741. https://doi.org/10.1109/TPAMI.1984.4767596

  10. Szu H, Hartley R (1987) Fast simulated annealing. Phys Lett A 122:157–162. https://doi.org/10.1016/0375-9601(87)90796-1

    Article  Google Scholar 

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Acknowledgements

The authors gratefully acknowledge financial support from the Ministry of Science, Innovation and Universities (RED2018-102518-T and PGC2018-098186-B-I00), the Spanish Research Agency (PID2020-118906GB-I00/AEI/10.13039/501100011033) and la Fundación la Caixa (2020/00062/001).

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Correspondence to José Ignacio Santos .

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Santos, J.I., Pereda, M., Ahedo, V., Galán, J.M. (2023). NetLogo Teaching Tool to Illustrate the Cooling Process in Simulated Annealing Using the Metropolis Model. In: Izquierdo, L.R., Santos, J.I., Lavios, J.J., Ahedo, V. (eds) Industry 4.0: The Power of Data. Lecture Notes in Management and Industrial Engineering. Springer, Cham. https://doi.org/10.1007/978-3-031-29382-5_3

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  • DOI: https://doi.org/10.1007/978-3-031-29382-5_3

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-29381-8

  • Online ISBN: 978-3-031-29382-5

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