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This paper investigates the effects of the manner of calculating the product cost price on forming the impact criteria in production program optimization in metalworking companies by means of genetic algorithms. An algorithm was defined for multiobjective production program optimization using genetic algorithms, with the application of nonlinear function of minimal costs and linear function for maximizing the machinery capacity level. The aim of the paper is to investigate the basic hypothesis that the manner of calculating the product cost price in metalworking companies within the framework of the goal to minimize the business operating costs has significant influence on the results obtained by applying genetic algorithms in production program optimization. The results of investigation indicate significant differences in an optimal production program gained by calculating the product cost price via traditional and activity-based costing approach to defining the nonlinear cost function, depending on the volume of production.