Project Scheduling: A Memetic Algorithm with Diversity-Adaptive Components that Optimizes the Effectiveness of Human Resources



Título del documento: Project Scheduling: A Memetic Algorithm with Diversity-Adaptive Components that Optimizes the Effectiveness of Human Resources
Revista: Polibits
Base de datos: PERIÓDICA
Número de sistema: 000402976
ISSN: 1870-9044
Autores: 1
1
Instituciones: 1Universidad Nacional del Centro de la Provincia de Buenos Aires, Instituto Superior de Ingeniería del Software de Tandil, Tandil, Buenos Aires. Argentina
Año:
Periodo: Jul-Dic
Número: 52
Paginación: 93-103
País: México
Idioma: Inglés
Tipo de documento: Artículo
Enfoque: Analítico
Resumen en inglés In this paper, a project scheduling problem is addressed. This problem supposes valuable assumptions about the effectiveness of human resources, and also considers a priority optimization objective for project managers. This objective is optimizing the effectiveness levels of the sets of human resources defined for the project activities. A memetic algorithm is proposed for solving the addressed problem. This memetic algorithm incorporates diversity-adaptive components into the framework of an evolutionary algorithm. The incorporation of these components is meant for improving the performance of the evolutionary-based search, in both exploitation and exploration. The performance of the memetic algorithm on instance sets with different complexity levels is compared with those of the heuristic search and optimization algorithms reported until now in the literature for the addressed problem. The results obtained from the performance comparison indicate that the memetic algorithm significantly outperforms the algorithms previously reported
Disciplinas: Ciencias de la computación,
Matemáticas
Palabras clave: Inteligencia artificial,
Programación,
Matemáticas aplicadas,
Algoritmos meméticos,
Recursos humanos,
Investigación de operaciones
Keyword: Computer science,
Mathematics,
Artificial intelligence,
Programming,
Applied mathematics,
Memetic algorithms,
Scheduling,
Human resources,
Operations research
Texto completo: Texto completo (Ver PDF)