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 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.