Parallel Genetic Algorithms for Finding Solution of System of Ordinary Differential Equations

  • Jane Jovanovski
  • Boro Jakimovski
  • Dragan Jakimovski
Conference paper
Part of the Advances in Intelligent and Soft Computing book series (AINSC, volume 150)


The goal of our research is to evaluate the general methods of finding solution of a system of differential equations. In this paper we investigate a novel two step genetic algorithm approach that produces an analytical solution of the system. The evaluation of the algorithm reveals its capability to solve non-trivial systems in very small number of generations. In order to find the best solution, and due to the fact that the simulations are computational intensive, we use grid genetic algorithms. Using the gLite based Grid, we propose a grid genetic solution that uses large number of computational nodes, that archives excellent performance. This research will be the basis on our goal of solving more complex research problems based around the Schrodingers equation.


Genetic Algorithm Candidate Solution Correct Solution Function Tree Grammatical Evolution 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag GmbH Berlin Heidelberg 2012

Authors and Affiliations

  • Jane Jovanovski
    • 1
  • Boro Jakimovski
    • 1
  • Dragan Jakimovski
    • 1
  1. 1.Faculty of Natural Sciences and MathematicsSs. Cyril and Methodius UniversitySkopjeMacedonia

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