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Adaptive Mutation-Driven Search for Global Minima in 3D Coulomb Clusters: A New Method with Preliminary Applications

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Proceedings of the Second International Conference on Soft Computing for Problem Solving (SocProS 2012), December 28-30, 2012

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 236))

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Abstract

A single-string-based evolutionary algorithm that adaptively learns to control the mutation probability \((p_m)\) and mutation intensity \((\Delta _m)\) has been developed and used to investigate the ground-state configurations and energetics of 3D clusters of a finite number (N) of ‘point-like’ charged particles. The particles are confined by a harmonic potential that is either isotropic or anisotropic. The energy per particle \((E_N/N)\) and its first and second differences are analyzed as functions of confinement anisotropy, to understand the nature of structural transition in these systems.

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References

  1. Zuzic, M., et al.: Phys. Rev. Lett. 85, 4064 (2000)

    Article  Google Scholar 

  2. Arp, O., Block, D., Piel, A., Melzer, A.: Phys. Rev. Lett. 93, 165004 (2004)

    Article  Google Scholar 

  3. Kählert, H., Bonitz, M.: Phys. Rev. Lett. 104, 015001 (2010)

    Article  Google Scholar 

  4. Buluta, I.M., Hasegawa, S.: Phys. Rev. A 78, 042340 (2008)

    Article  Google Scholar 

  5. Apolinario, S.W.S., Peeters, F.M.: Phys. Rev. E 83, 041136 (2011)

    Article  Google Scholar 

  6. Holland, J.H.: Adaptation in Natural and Artificial Systems: An Introductory Analysis with Applications to Biology, Control and Artificial Intelligence. MIT Press, Cambridge, MA, USA (1992)

    Google Scholar 

  7. Sobczak, P., Kucharski, L., Kamieniarz, G.: Comput. Phys. Commun. 182, 1900 (2011)

    Article  Google Scholar 

  8. Ali, M., Smith, R., Hobday, S.: Comput. Phys. Commun. 175, 451 (2006)

    Article  MATH  MathSciNet  Google Scholar 

  9. Nandy, S., Sharma, R., Bhattacharyya, S.P.: Appl. Soft Comput. 11, 3946 (2011)

    Article  Google Scholar 

  10. Kirkpatrick, S., Gelatt, C.D., Vecchi, M.P.: Science 220, 671 (1983)

    Article  MATH  MathSciNet  Google Scholar 

  11. Li, Z., Scheraga, H.A.: Proc. Nat. Acad. Sci. 84, 6611 (1987)

    Article  MathSciNet  Google Scholar 

  12. Mitchell, M., Holland, J.H., Forrest, S.: When will a genetic algorithm outperform hill climbing?. In: Advances in Neural Information Processing Systems, vol. 6, pp. 51–58, Morgan Kaufmann, (1993)

    Google Scholar 

  13. Sharma, R., Bhattacharyya, S.P.: Direct search for wave operator by a genetic algorithm (ga): route to few eigenvalues of a hamiltonian. In: IEEE Congress on, Evolutionary Computation, pp. 3812–3817, (2007)

    Google Scholar 

  14. Sarkar, K., Sharma, R., Bhattacharyya, S.P.: J. Chem. Theory Comput. 6, 718 (2010)

    Article  Google Scholar 

  15. Sarkar, K., Sharma, R., Bhattacharyya, S.P.: Int. J. Quantum Chem. 112, 1547 (2012)

    Article  Google Scholar 

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Acknowledgments

K. Sarkar thanks the CSIR, Government of India, New Delhi, for the award of senior research fellowship, and S.P.B. thanks the DAE, Government of India, for the award of Raja Ramanna Fellowship.

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Authors and Affiliations

  1. IIT Bombay, Mumbai, 400076, India

    S. P. Bhattacharyya

  2. Indian Association for the Cultivation of Science, Jadavpur, Kolkata, 700032, India

    Kanchan Sarkar

Authors
  1. S. P. Bhattacharyya
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  2. Kanchan Sarkar
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Corresponding author

Correspondence to S. P. Bhattacharyya .

Editor information

Editors and Affiliations

  1. Institute of Engineering and Technology, JK Lakshmipat University, Jaipur, Rajasthan, India

    B. V. Babu

  2. Department of Computer Science, Liverpool Hope University, Liverpool, United Kingdom

    Atulya Nagar

  3. Department of Mathematics, Indian Institute of Technology Roorkee, Roorkee, Uttarakhand, India

    Kusum Deep

  4. Department of Paper Technology, Indian Institute of Technology Roorkee, Roorkee, India

    Millie Pant

  5. Department of Applied Mathematics, South Asian University, New Delhi, India

    Jagdish Chand Bansal

  6. Institute of Engineering and Technology, JK Lakshmipat University, Jaipur, Rajasthan, India

    Kanad Ray

  7. Institute of Engineering and Technology, JK Lakshmipat University, Jaipur, Rajasthan, India

    Umesh Gupta

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Bhattacharyya, S. ., Sarkar, K. (2014). Adaptive Mutation-Driven Search for Global Minima in 3D Coulomb Clusters: A New Method with Preliminary Applications. In: Babu, B., et al. Proceedings of the Second International Conference on Soft Computing for Problem Solving (SocProS 2012), December 28-30, 2012. Advances in Intelligent Systems and Computing, vol 236. Springer, New Delhi. https://doi.org/10.1007/978-81-322-1602-5_129

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  • DOI: https://doi.org/10.1007/978-81-322-1602-5_129

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  • Publisher Name: Springer, New Delhi

  • Print ISBN: 978-81-322-1601-8

  • Online ISBN: 978-81-322-1602-5

  • eBook Packages: EngineeringEngineering (R0)

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