ENHANCING PRODUCTION AND SALE BASED ON MATHEMATICAL STATISTICS AND THE GENETIC ALGORITHM

Snezana Nestic¹, Aleksandar Aleksic¹, Jaime Gil Lafuente² and Nikolina Ljepava³

¹University of Kragujevac, Faculty of Engineering, Kragujevac, The Republic of Serbia
²University of Barcelona, Faculty of Economics and Business Science, Barcelona, Spain
³American University in the Emirates, Dubai International Academic City, United Arab Emirates

Enhancing production and sale has a very significant effect on the competitive advantage of any production enterprise. In practice, especially in companies with highly diversified production, products have a different impact on generating revenue. Therefore, operational management pay attention to the products of the utmost importance. The Pareto analysis is the most broadly used product classification method. It can be said that the results obtained by this analysis are still very burdened by decision-makers’ subjective attitudes. This paper proposes a model for selecting products with the biggest impact on generating revenue in an exact way. In the model’s first stage, whether there is a linear relationship between volume demand and a discounted amount is analyzed applying mathematical statistics methods. In the second stage, the Genetic Algorithm (GA) method is proposed so as to obtain a near-optimal set of the most important products. The proposed model is shown to be a useful and effective assessment tool for sales and operational management in a production enterprise.

Keywords: product portfolio selection, enhancing production and sale, descriptive statistics, regression analysis, genetic algorithm

JEL Classification: C40, C61