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Global Transformer Design Optimization Using Deterministic and Nondeterministic Algorithms

delete2014-01-01
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PRE
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E
Eleftherios I. Amoiralis *
D
Dimitrios G. Paparigas
A
Antonios G. Kladas
DOI:10.1109/TIA.2013.2288417delete
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Abstract

Abstract

En 中文
This paper compares the application of two deterministic and three nondeterministic optimization algorithms to global transformer design optimization (TDO). Two deterministic optimization algorithms (mixed-integer nonlinear programming and heuristic algorithm) are compared to three nondeterministic approaches (harmony search, differential evolution, and genetic algorithm). All these algorithms are integrated in design optimization software applied and verified in the manufacturing industry. The comparison yields significant conclusions on the efficiency of the algorithms and the selection of the most suitable one for the TDO problem.
Keywords:
Algorithms
artificial intelligence
design for manufacture
design methodology
design optimization
genetic algorithms (GAs)
heuristic algorithms (HAs)
optimization methods
power transformers
software packages
transformers
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Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.

Journal

IEEE Transactions on Industry Applications cover
IEEE Transactions on Industry Applications
IF:
4.5
Papers:
1.1W
Citations:
3.5W

Organization

N
National Technical University of Athens
Scholars:
9.7K
Papers: 9.5K
Citations: 8.2K
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