Abstract
For a qualitatively and quantitatively analysis of a complex Decision Making (DM) process is critical to employ a correct method due to the large number of operations required. This paper presents an approach employing Binary Decision Diagram (BDD) applied to the Logical Decision Tree. LDT allows addressing a Main Problem (MP) by establishing different causes, called Basic Causes (BC) and their interrelations. The cases that have a large number of BCs generate important computational costs because it is a NP-hard type problem. This paper presents a new approach in order to analyze big LDT. A new approach to reduce the complexity of the problem is hereby presented. It makes use of data derived from simpler problems that requires less computational costs for obtaining a good solution. An exact solution is not provided by this method but the approximations achieved have a low deviation from the exact.
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Acknowledgments
The work reported herewith has been financially supported by the Spanish Ministerio de Economía y Competitividad, under Research Grant DPI2012-31579.
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Marugán, A.P., Márquez, F.P.G. (2015). Improving the Efficiency on Decision Making Process via BDD. In: Xu, J., Nickel, S., Machado, V., Hajiyev, A. (eds) Proceedings of the Ninth International Conference on Management Science and Engineering Management. Advances in Intelligent Systems and Computing, vol 362. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-47241-5_116
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DOI: https://doi.org/10.1007/978-3-662-47241-5_116
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