A Metaheuristic Optimization Algorithm for Solving Higher-Order Boundary Value Problems

Shaza Alturky, George Albert Toma

Source Title: International Journal of Applied Metaheuristic Computing (IJAMC)13(1)

ISSN: 1947-8283|EISSN: 1947-8291|EISBN13: 9781799885405|DOI: 10.4018/IJAMC.292515

MLA

Alturky, Shaza, and George Albert Toma. "A Metaheuristic Optimization Algorithm for Solving Higher-Order Boundary Value Problems." IJAMC vol.13, no.1 2022: pp.1-17. http://doi.org/10.4018/IJAMC.292515

APA

Alturky, S. & Toma, G. A. (2022). A Metaheuristic Optimization Algorithm for Solving Higher-Order Boundary Value Problems. International Journal of Applied Metaheuristic Computing (IJAMC), 13(1), 1-17. http://doi.org/10.4018/IJAMC.292515

Chicago

Alturky, Shaza, and George Albert Toma. "A Metaheuristic Optimization Algorithm for Solving Higher-Order Boundary Value Problems," International Journal of Applied Metaheuristic Computing (IJAMC) 13, no.1: 1-17. http://doi.org/10.4018/IJAMC.292515

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Abstract

An effective metaheuristic algorithm to solve the higher-order boundary value problems, called a genetic programming technique is presented. In this paper, a genetic programming algorithm, which depends on the syntax tree representation, is employed to obtain the analytical solutions of higher- order differential equations with the boundary conditions. The proposed algorithm can be produce an exact or approximate solution when the classical methods lead to unsatisfactory results. To illustrate the efficiency and accuracy of the designed algorithm, several examples are tested. Finally, the obtained results are compared with the existing methods such as the homotopy analysis method, the B-Spline collocation method and the differential transform method.