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A GA-Simplex Hybrid Algorithm for Global Minimization of Molecular Potential Energy Functions

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  • Helio Barbosa
  • Carlile Lavor
  • Fernanda Raupp

Abstract

In this paper we propose a hybrid genetic algorithm for minimizing molecular potential energy functions. Experimental evidence shows that the global minimum of the potential energy of a molecule corresponds to its most stable conformation, which dictates its properties. The search for the global minimum of a potential energy function is very difficult since the number of local minima grows exponentially with molecule size. The proposed approach was successfully applied to two cases: (i) a simplified version of more general molecular potential energy functions in problems with up to 100 degrees of freedom, and (ii) a realistic potential energy function modeling two different molecules. Copyright Springer Science + Business Media, Inc. 2005

Suggested Citation

  • Helio Barbosa & Carlile Lavor & Fernanda Raupp, 2005. "A GA-Simplex Hybrid Algorithm for Global Minimization of Molecular Potential Energy Functions," Annals of Operations Research, Springer, vol. 138(1), pages 189-202, September.
    • Handle: RePEc:spr:annopr:v:138:y:2005:i:1:p:189-202:10.1007/s10479-005-2453-2
    DOI: 10.1007/s10479-005-2453-2
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    Cited by:

    1. L. Yang & T. Yang, 2015. "Energy consumption and economic growth from perspective of spatial heterogeneity: statistical analysis based on variable coefficient model," Annals of Operations Research, Springer, vol. 228(1), pages 151-161, May.
    2. Drazic, Milan & Lavor, Carlile & Maculan, Nelson & Mladenovic, Nenad, 2008. "A continuous variable neighborhood search heuristic for finding the three-dimensional structure of a molecule," European Journal of Operational Research, Elsevier, vol. 185(3), pages 1265-1273, March.

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