Solving initial and boundary value problems using learning automata particle swarm optimization
In this article, the particle swarm optimization (PSO) algorithm is modified to use the learning automata (LA) technique for solving initial and boundary value problems. A constrained problem is converted into an unconstrained problem using a penalty method to define an appropriate fitness function,...
| Main Authors: | , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Taylor and Francis Ltd.
2015
|
| Subjects: | |
| Online Access: | http://eprints.utm.my/56028/1/KouroshNemati2015_SolvingInitialandBoundaryValueProblemsUsingLearningAutomata.pdf |
| _version_ | 1796860307929300992 |
|---|---|
| author | Nemati, Kourosh Shamsuddin, Siti Mariyam Darus, M. |
| author_facet | Nemati, Kourosh Shamsuddin, Siti Mariyam Darus, M. |
| author_sort | Nemati, Kourosh |
| collection | ePrints |
| description | In this article, the particle swarm optimization (PSO) algorithm is modified to use the learning automata (LA) technique for solving initial and boundary value problems. A constrained problem is converted into an unconstrained problem using a penalty method to define an appropriate fitness function, which is optimized using the LA-PSO method. This method analyses a large number of candidate solutions of the unconstrained problem with the LA-PSO algorithm to minimize an error measure, which quantifies how well a candidate solution satisfies the governing ordinary differential equations (ODEs) or partial differential equations (PDEs) and the boundary conditions. This approach is very capable of solving linear and nonlinear ODEs, systems of ordinary differential equations, and linear and nonlinear PDEs. The computational efficiency and accuracy of the PSO algorithm combined with the LA technique for solving initial and boundary value problems were improved. Numerical results demonstrate the high accuracy and efficiency of the proposed method. |
| first_indexed | 2024-03-05T19:39:25Z |
| format | Article |
| id | utm.eprints-56028 |
| institution | Universiti Teknologi Malaysia - ePrints |
| language | English |
| last_indexed | 2024-03-05T19:39:25Z |
| publishDate | 2015 |
| publisher | Taylor and Francis Ltd. |
| record_format | dspace |
| spelling | utm.eprints-560282016-11-15T07:07:27Z http://eprints.utm.my/56028/ Solving initial and boundary value problems using learning automata particle swarm optimization Nemati, Kourosh Shamsuddin, Siti Mariyam Darus, M. QA75 Electronic computers. Computer science In this article, the particle swarm optimization (PSO) algorithm is modified to use the learning automata (LA) technique for solving initial and boundary value problems. A constrained problem is converted into an unconstrained problem using a penalty method to define an appropriate fitness function, which is optimized using the LA-PSO method. This method analyses a large number of candidate solutions of the unconstrained problem with the LA-PSO algorithm to minimize an error measure, which quantifies how well a candidate solution satisfies the governing ordinary differential equations (ODEs) or partial differential equations (PDEs) and the boundary conditions. This approach is very capable of solving linear and nonlinear ODEs, systems of ordinary differential equations, and linear and nonlinear PDEs. The computational efficiency and accuracy of the PSO algorithm combined with the LA technique for solving initial and boundary value problems were improved. Numerical results demonstrate the high accuracy and efficiency of the proposed method. Taylor and Francis Ltd. 2015-05-04 Article PeerReviewed application/pdf en http://eprints.utm.my/56028/1/KouroshNemati2015_SolvingInitialandBoundaryValueProblemsUsingLearningAutomata.pdf Nemati, Kourosh and Shamsuddin, Siti Mariyam and Darus, M. (2015) Solving initial and boundary value problems using learning automata particle swarm optimization. Engineering Optimization, 47 (5). pp. 656-673. ISSN 0305-215X http://dx.doi.org/10.1080/0305215X.2014.914190 DOI:10.1080/0305215X.2014.914190 |
| spellingShingle | QA75 Electronic computers. Computer science Nemati, Kourosh Shamsuddin, Siti Mariyam Darus, M. Solving initial and boundary value problems using learning automata particle swarm optimization |
| title | Solving initial and boundary value problems using learning automata particle swarm optimization |
| title_full | Solving initial and boundary value problems using learning automata particle swarm optimization |
| title_fullStr | Solving initial and boundary value problems using learning automata particle swarm optimization |
| title_full_unstemmed | Solving initial and boundary value problems using learning automata particle swarm optimization |
| title_short | Solving initial and boundary value problems using learning automata particle swarm optimization |
| title_sort | solving initial and boundary value problems using learning automata particle swarm optimization |
| topic | QA75 Electronic computers. Computer science |
| url | http://eprints.utm.my/56028/1/KouroshNemati2015_SolvingInitialandBoundaryValueProblemsUsingLearningAutomata.pdf |
| work_keys_str_mv | AT nematikourosh solvinginitialandboundaryvalueproblemsusinglearningautomataparticleswarmoptimization AT shamsuddinsitimariyam solvinginitialandboundaryvalueproblemsusinglearningautomataparticleswarmoptimization AT darusm solvinginitialandboundaryvalueproblemsusinglearningautomataparticleswarmoptimization |