Improving the Efficiency on Decision Making Process via BDD
For a qualitatively and quantitatively analysis of a complex Decision Mak- ing (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...
| Autores: | , |
|---|---|
| Tipo de recurso: | artículo |
| Fecha de publicación: | 2015 |
| País: | España |
| Institución: | Universidad de Castilla-La Mancha |
| Repositorio: | RUIdeRA. Repositorio Institucional de la UCLM |
| OAI Identifier: | oai:ruidera.uclm.es:10578/12192 |
| Acceso en línea: | http://hdl.handle.net/10578/12192 |
| Access Level: | acceso abierto |
| Palabra clave: | Efficiency Binary Decision Diagrams |
| Sumario: | For a qualitatively and quantitatively analysis of a complex Decision Mak- ing (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 complex- ity 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. |
|---|