Optimization Solution of Troesch's and Bratu's Problems of Ordinary Type Using Novel Continuous Genetic Algorithm

A new kind of optimization technique, namely, continuous genetic algorithm, is presented in this paper for numerically approximating the solutions of Troesch’s and Bratu’s problems. The underlying idea of the method is to convert the two differential problems into discrete versions by replacing each...

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Bibliographic Details
Published in:Discrete Dynamics in Nature and Society 2014-01, Vol.2014 (2014), p.52-66-105
Main Authors: Abo-Hammour, Zaer, Abu Arqub, Omar, Momani, Shaher M., Shawagfeh, Nabil
Format: Article
Language:English
Subjects:
Algorithms
Applied mathematics
Approximation
Boundary conditions
Colleges & universities
Derivatives
Differential equations
Digital computers
Dynamics
Functions, Continuous
Genetic algorithms
Mathematical analysis
Mathematical models
Mathematical research
Mathematics
Methods
Numerical analysis
Optimization
Optimization techniques
Ordinary differential equations
Science
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Summary:A new kind of optimization technique, namely, continuous genetic algorithm, is presented in this paper for numerically approximating the solutions of Troesch’s and Bratu’s problems. The underlying idea of the method is to convert the two differential problems into discrete versions by replacing each of the second derivatives by an appropriate difference quotient approximation. The new method has the following characteristics. First, it should not resort to more advanced mathematical tools; that is, the algorithm should be simple to understand and implement and should be thus easily accepted in the mathematical and physical application fields. Second, the algorithm is of global nature in terms of the solutions obtained as well as its ability to solve other mathematical and physical problems. Third, the proposed methodology has an implicit parallel nature which points to its implementation on parallel machines. The algorithm is tested on different versions of Troesch’s and Bratu’s problems. Experimental results show that the proposed algorithm is effective, straightforward, and simple.
ISSN:1026-0226
1607-887X
DOI:10.1155/2014/401696