Global Transformer Design Optimization Using Deterministic and Nondeterministic Algorithms

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...

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Bibliographic Details
Published in:IEEE transactions on industry applications Vol. 50; no. 1; pp. 383 - 394
Main Authors: Amoiralis, Eleftherios I., Tsili, Marina A., Paparigas, Dimitrios G., Kladas, Antonios G.
Format: Journal Article
Language:English
Published: New York IEEE 01.01.2014
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:
Algorithm design and analysis
Algorithms
artificial intelligence
Computer programs
design for manufacture
design methodology
Design optimization
Evolution
genetic algorithms (GAs)
heuristic algorithms (HAs)
Nonlinear programming
Optimization
optimization methods
Power transformer insulation
power transformers
Software
software packages
Transformers
Vectors
Windings
ISSN:0093-9994, 1939-9367
Online Access:Get full text
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Summary: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.
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ISSN:0093-9994
1939-9367
DOI:10.1109/TIA.2013.2288417