Browsing by Author "Abadic, Nebojsa"

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    Determination of the effectiveness of the realization of enterprise business objectives and improvement strategies in an uncertain environment
    (2015) Stefanovic, Miladin; Tadić, Danijela; Arsovski S.; Pravdic P.; Abadic, Nebojsa; Stefanovic, Nikola
    © 2015 Wiley Publishing Ltd. This study determines the effectiveness of business objectives and key performance indicators (KPIs) of the identified business objectives for different types of enterprise. The evaluations of the relative importance of KPIs are called a fuzzy group-decision-making problem. The KPI weights are determined using the fuzzy analytic hierarchical process. The effectiveness of business objectives and KPIs is determined using the adopted Balanced Scorecard Designer Pro. Determination of the KPI rank with respect to each enterprise type is on the basis of Pareto analysis. The priority of management initiatives of the improvement strategy corresponds to the calculated rank, and it has a critical effect on the competitive advantage of any enterprise. The results discuss manufacturing, public and service enterprises, which exist in central Serbia. The proposed approach can also be adapted to different businesses.
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    Production process parameter optimization with a new model based on a genetic algorithm and ABC classification method
    (2016) Eric M.; Stefanovic, Miladin; Djordjevic, Aleksandar; Stefanovic N.; Mišić, Milan; Abadic, Nebojsa; Popovic P.
    © The Author(s) 2016. The difference between the production cost and selling price of the products may be viewed as a criterion that determines an organization's competitiveness and market success. In such circumstances, it is necessary to impact these criteria in order to maximize this difference. The selling products' price, in modern market conditions, is a category which may not be significantly affected. So organizations have one option, which is the production cost reduction. This is the motive for business organizations and the imperative of each organization. The key parameters that influence the costs of production and therefore influence the competitiveness of organizations are the parameters of production machines and processes used to create products. To define optimal parameter values for production machines and processes that will reduce production costs and increase competitiveness of production organizations, the authors have developed a new mathematical model. The model is based on application of the ABC classification method to classify production line processes based on their costs and an application of a genetic algorithm to find the optimal values of production machine parameters used in these processes. It has been applied in three different modern production line processes; the costs obtained by the model application have been compared with the real production costs.