Model Genetic Rules Based Systems for Evaluation of Projects | Zendy

Jesus Silva | Zendy; John Freddy Escobar Gomez | Zendy; Ernesto Steffens Sanabria | Zendy; Hugo Hernández Palma | Zendy; Midori Ikeda | Zendy; Jorge Linares | Zendy; Nohora Mercado | Zendy

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Model Genetic Rules Based Systems for Evaluation of Projects

Author(s) -

Jesus Silva,

John Freddy Escobar Gomez,

Ernesto Steffens Sanabria,

Hugo Hernández Palma,

Midori Ikeda,

Jorge Linares,

Nohora Mercado

Publication year - 2020

Publication title -

procedia computer science

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.334

H-Index - 76

ISSN - 1877-0509

DOI - 10.1016/j.procs.2020.03.069

Subject(s) - computer science , genetic programming , process (computing) , genetic algorithm , control (management) , evolutionary algorithm , operations research , management science , artificial intelligence , machine learning , engineering , economics , operating system

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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