Solving many real world combinatorial optimization problems has involved a wide variety of effective genetic algorithms and their variants. Combinatorial optimization techniques applied in design of electrical high power equipment can bring great savings of electric energy in the distribution network and also reduce the cost and time of manufacturing of the equipment itself. In that regard, special interest is given to the minimization of production costs of power objects. In the work presented in this paper are described different techniques of optimization and applied to minimizing the production cost of the active part of power objects. This paper gives a detailed comparative analysis of Constrained non-linear minimization (CN), Genetic Algorithms (GA) and Differential Evolution Algorithms (DE) results. Constraints stemming from international standards and specifications and also customer requirements are taken into account. The Objective Function that is optimized is a minimization dependent on multiple configurable input variables. All constraints are normalized and modeled as inequalities.
Combinatorial optimization, Constrained non-linear minimization, Genetic Algorithms, Differential Evolution Algorithms , Optimization methods, Distribution transformer, Wound core type transformer.