Optimizing the dynamic response of the H. B. Robinson nuclear plant using multiobjective particle swarm optimization
| Autor: | M. A. Elsays, M. Naguib Aly, Alya Badawi |
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| Rok vydání: | 2009 |
| Předmět: |
Nuclear and High Energy Physics
Mathematical optimization Radiation Computer Science::Neural and Evolutionary Computation MathematicsofComputing_NUMERICALANALYSIS Pareto principle Particle swarm optimization Nonlinear system Algebraic equation Nuclear Energy and Engineering Ordinary differential equation Initial value problem General Materials Science Multi-swarm optimization Safety Risk Reliability and Quality Interpolation Mathematics |
| Zdroj: | Kerntechnik. 74:70-78 |
| ISSN: | 2195-8580 0932-3902 |
| DOI: | 10.3139/124.110010 |
| Popis: | In this paper, the Particle Swarm Optimization (PSO) algorithm is modified to deal with Multiobjective Optimization Problems (MOPs). A mathematical model for predicting the dynamic response of the H. B. Robinson nuclear power plant, which represents an Initial Value Problem (IVP) of Ordinary Differential Equations (ODEs), is solved using Runge-Kutta formula. The resulted data values are represented as a system of nonlinear algebraic equations by interpolation schemes for data fitting. This system of fitted nonlinear algebraic equations represents a nonlinear multiobjective optimization problem. A Multiobjective Particle Swarm Optimizer (MOPSO) which is based on the Pareto optimality concept is developed and applied to maximize the above mentioned problem. Results show that MOPSO efficiently cope with the problem and finds multiple Pareto optimal solutions. |
| Databáze: | OpenAIRE |
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