Model genetic rules based systems for evaluation of projects
The process of project evaluation is of vital importance for decision-making in organizations. In the particular case of IT projects, the historical average of successful projects is 30.7%, while renegotiated projects are 47.3% and cancelled projects are 22% [1]. These figures mean that huge budgets...
- Autores:
-
Silva, Jesus
Escobar Gomez, John Freddy
Steffens Sanabria, Ernesto
hernandez Palma, Hugo
Ikeda Tsukazan, Lucía Midori
Linares Weilg, Jorge Luis
Mercado, Nohora
- Tipo de recurso:
- Article of journal
- Fecha de publicación:
- 2021
- Institución:
- Corporación Universidad de la Costa
- Repositorio:
- REDICUC - Repositorio CUC
- Idioma:
- eng
- OAI Identifier:
- oai:repositorio.cuc.edu.co:11323/7800
- Acceso en línea:
- https://hdl.handle.net/11323/7800
https://doi.org/10.1016/j.procs.2020.03.069
https://repositorio.cuc.edu.co/
- Palabra clave:
- Genetic Algorithms
Gene Expression Programming
MCGEP Algorithm
Project Evaluation
Rules learning
- Rights
- openAccess
- License
- Attribution-NonCommercial-NoDerivatives 4.0 International
| Summary: | The process of project evaluation is of vital importance for decision-making in organizations. In the particular case of IT projects, the historical average of successful projects is 30.7%, while renegotiated projects are 47.3% and cancelled projects are 22% [1]. These figures mean that huge budgets are affected every year by errors in planning or control and monitoring of projects, with an economic and social impact. The objective of this research is to evaluate the MCGEP evolutionary algorithm in different versions databases with information on the evaluation of IT projects. The aim is to determine the possibility of applying an evolutionary algorithm that uses programming of genetic expressions as opposed to others of greater use. |
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