These tools will no longer be maintained as of December 31, 2024. Archived website can be found here. PubMed4Hh GitHub repository can be found here. Contact NLM Customer Service if you have questions.


PUBMED FOR HANDHELDS

Search MEDLINE/PubMed


  • Title: The merits of a parallel genetic algorithm in solving hard optimization problems.
    Author: van Soest AJ, Casius LJ.
    Journal: J Biomech Eng; 2003 Feb; 125(1):141-6. PubMed ID: 12661208.
    Abstract:
    A parallel genetic algorithm for optimization is outlined, and its performance on both mathematical and biomechanical optimization problems is compared to a sequential quadratic programming algorithm, a downhill simplex algorithm and a simulated annealing algorithm. When high-dimensional non-smooth or discontinuous problems with numerous local optima are considered, only the simulated annealing and the genetic algorithm, which are both characterized by a weak search heuristic, are successful in finding the optimal region in parameter space. The key advantage of the genetic algorithm is that it can easily be parallelized at negligible overhead.
    [Abstract] [Full Text] [Related] [New Search]