Title :
Optimization of strategic level performance measurement and decision making using artificial neural network
Author :
Németh, Péter ; Földesi, Péter ; Tápler, Csaba ; Botzheim, János
Author_Institution :
Dept. of Logistics & Forwarding, Szechenyi Istvan Univ., Gyor, Hungary
Abstract :
In our paper we propose a new method for the strategic level performance measurement and decision making by presenting two case studies performed in 2011. We proposed a computational intelligence method to establish connection between basic operational level data and important strategic level indicators. In the first case study this indicator is related to performance measurement. In the second case study the indicator is the contribution margin of the given company. After the introduction we present the process of programming and learning with actual company data. Finally an evaluation of the results is presented based on the program runs.
Keywords :
decision support systems; neural nets; optimisation; production engineering computing; strategic planning; supply chain management; artificial neural network; computational intelligence method; decision making; operational level data; strategic level indicators; strategic level performance measurement optimization; supply chain management; Artificial neural networks; Companies; Measurement; Memetics; Microorganisms; Neurons; Training;
Conference_Titel :
Technology Management Conference (ITMC), 2012 IEEE International
Conference_Location :
Dallas, TX
Print_ISBN :
978-1-4673-2133-4
Electronic_ISBN :
978-1-4673-2132-7
DOI :
10.1109/ITMC.2012.6306360