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Fuzzy Chemical Reaction Algorithm with Dynamic Adaptation of Parameters

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Fuzzy Logic in Intelligent System Design (NAFIPS 2017)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 648))

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Abstract

In this research work, we used the Chemical Reaction Algorithm (CRA) for solving optimization problems. The used optimization algorithm is based on an abstraction of chemical reactions. The main goal of the method is to dynamically adjust the parameters of the reactions in the range from 0.1 to 1. The impact of using fixed parameters in the CRA is discussed and then a strategy for efficiently tuning these parameters using fuzzy logic is presented. The Fuzzy CRA algorithm was successfully applied on different benchmarking optimization problems. The results of simulations and comparison studies demonstrate the effectiveness and efficiency of the proposed approach.

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References

  1. Amador-Angulo, L., Castillo, O.: Comparison of the optimal design of fuzzy controllers for the water tank using ant colony optimization. In: Recent Advances on Hybrid Approaches for Designing Intelligent Systems, pp. 255–273. Springer International Publishing (2014)

    Google Scholar 

  2. Amador-Angulo, L., Castillo, O.: A fuzzy bee colony optimization algorithm using an interval type-2 fuzzy logic system for trajectory control of a mobile robot. In: Mexican International Conference on Artificial Intelligence, pp. 460–471. Springer International Publishing, October 2015

    Google Scholar 

  3. Astudillo, L., Castillo, O., Aguilar, L., Martínez, R.: Hybrid control for an autonomous wheeled mobile robot under perturbed torques. In: IFSA, vol. 1, pp. 594–603 (2007)

    Google Scholar 

  4. Astudillo L., Castillo O., Aguilar L.: Intelligent control of an autonomous mobile robot using Type-2 fuzzy logic. In: IC-AI 2006, pp. 565–570 (2006)

    Google Scholar 

  5. Astudillo, L., Melin, P., Castillo, O.: A new optimization method based on a paradigm inspired by nature. In: Soft Computing for Recognition Based on Biometrics, pp. 277–283. Springer, Heidelberg (2010)

    Google Scholar 

  6. Astudillo, L., Melin, P., Castillo, O.: Nature inspired chemical optimization to design a type-2 fuzzy controller for a mobile robot. In: 2013 Joint IFSA World Congress and NAFIPS Annual Meeting (IFSA/NAFIPS), pp. 1423–1428. IEEE, June 2013

    Google Scholar 

  7. Castillo, O., Martinez, R., Melin, P., Valdez, F., Soria, J.: Comparative study of bio-inspired algorithms applied to the optimization of type-1 and type-2 fuzzy controllers for an autonomous mobile robot. Inf. Sci. 192, 19–38 (2012)

    Article  Google Scholar 

  8. Cervantes L., Castillo O.: Design of a fuzzy system for the longitudinal control of an F-14 airplane. In: Soft Computing for Intelligent Control and Mobile Robotics 2011, pp. 213–224 (2011)

    Google Scholar 

  9. de la O, D., Castillo, D., Soria, J.: Optimization of reactive control for mobile robots based on the CRA using Type-2 fuzzy logic. Stud. Comput. Intell 667(1), 505–518 (2017)

    Google Scholar 

  10. de la O, D., Castillo, O., Melendez, A., Astudillo, L.: Optimization of a reactive controller for mobile robots based on CRA. In: 2015 Annual Conference of the North American Fuzzy Information Processing Society (NAFIPS) held Jointly with 2015 5th World Conference on Soft Computing (WConSC), pp. 1–6. IEEE, August 2015

    Google Scholar 

  11. Fierro, R., Castillo, O., Valdez, F., Cervantes, L.: Design of optimal membership functions for fuzzy controllers of the water tank and inverted pendulum with PSO variants. In: 2013 Joint IFSA World Congress and NAFIPS Annual Meeting (IFSA/NAFIPS), pp. 1068–1073. IEEE, June 2013

    Google Scholar 

  12. Fang, G., Kwok, N.M., Ha, Q.: Automatic fuzzy membership function tuning using the particle swarm optimization. In: PACIIA 2008, Pacific-Asia Workshop on Computational Intelligence and Industrial Application, 19–20 December 2008, vol. 2, pp. 324–328 (2008)

    Google Scholar 

  13. Li, H.X., Gatland, H.B.: A new methodology for designing a fuzzy logic controller. IEEE Trans. Syst. Man Cybern. 25(3), 505–512 (1995)

    Article  Google Scholar 

  14. Milla, F., Sáez, D., Cortés, C.E., Cipriano, A.: Bus-stop control strategies based on fuzzy rules for the operation of a public transport system. IEEE Trans. Intell. Transp. Syst. 13(3), 1394–1403 (2012)

    Article  Google Scholar 

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Acknowledgment

We would like to express our gratitude to CONACYT, and Tijuana Institute of Technology for the facilities and resources granted for the development of this research.

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Authors and Affiliations

  1. Division of Graduate Studies and Research, Tijuana Institute of Technology, Tijuana, Mexico

    David de la O, Oscar Castillo, Leslie Astudillo & Jose Soria

Authors
  1. David de la O
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  2. Oscar Castillo
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  3. Leslie Astudillo
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  4. Jose Soria
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Corresponding author

Correspondence to Oscar Castillo .

Editor information

Editors and Affiliations

  1. Division of Graduate Studies and Research, Tijuana Institute of Technology, Tijuana, Baja California, Mexico

    Patricia Melin

  2. Division of Graduate Studies and Research, Tijuana Institute of Technology, Tijuana, Baja California, Mexico

    Oscar Castillo

  3. Systems Research Institute, Polish Academy of Sciences, Warsaw, Poland

    Janusz Kacprzyk

  4. Department of Electrical and Computer Engineering, University of Alberta, Edmonton, Alberta, Canada

    Marek Reformat

  5. Laboratory of Computational Intelligence and Automation, University of Waterloo, Waterloo, Ontario, Canada

    William Melek

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de la O, D., Castillo, O., Astudillo, L., Soria, J. (2018). Fuzzy Chemical Reaction Algorithm with Dynamic Adaptation of Parameters. In: Melin, P., Castillo, O., Kacprzyk, J., Reformat, M., Melek, W. (eds) Fuzzy Logic in Intelligent System Design. NAFIPS 2017. Advances in Intelligent Systems and Computing, vol 648. Springer, Cham. https://doi.org/10.1007/978-3-319-67137-6_13

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  • DOI: https://doi.org/10.1007/978-3-319-67137-6_13

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-67136-9

  • Online ISBN: 978-3-319-67137-6

  • eBook Packages: EngineeringEngineering (R0)

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