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Artículo

Project scheduling: A multi-objective evolutionary algorithm that optimizes the effectiveness of human resources and the project makespan

Yannibelli, Virginia DanielaIcon ; Amandi, Analia AdrianaIcon
Fecha de publicación: 04/2012
Editorial: Taylor & Francis
Revista: Engineering Optimization
ISSN: 0305-215X
Idioma: Inglés
Tipo de recurso: Artículo publicado
Clasificación temática:
Ciencias de la Computación

Resumen

In this article, the project scheduling problem is addressed in order to assist project managers at the early stage of scheduling. Thus, as part of the problem, two priority optimization objectives for managers at that stage are considered. One of these objectives is to assign the most effective set of human resources to each project activity. The effectiveness of a human resource is considered to depend on its work context. The other objective is to minimize the project makespan. To solve the problem, a multi-objective evolutionary algorithm is proposed. This algorithm designs feasible schedules for a given project and evaluates the designed schedules in relation to each objective. The algorithm generates an approximation to the Pareto set as a solution to the problem. The computational experiments carried out on nine different instance sets are reported.
Palabras clave: Project Scheduling , Human Resource Assignement , Multi-Skilled Resources , Effectiveness of Human Resources
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info:eu-repo/semantics/openAccess Excepto donde se diga explícitamente, este item se publica bajo la siguiente descripción: Creative Commons Attribution-NonCommercial-ShareAlike 2.5 Unported (CC BY-NC-SA 2.5)
Identificadores
URI: http://hdl.handle.net/11336/33188
DOI: http://dx.doi.org/10.1080/0305215X.2012.658782
URL: http://www.tandfonline.com/doi/abs/10.1080/0305215X.2012.658782
Colecciones
Articulos(CCT - TANDIL)
Articulos de CTRO CIENTIFICO TECNOLOGICO CONICET - TANDIL
Articulos(ISISTAN)
Articulos de INSTITUTO SUPERIOR DE INGENIERIA DEL SOFTWARE
Citación
Amandi, Analia Adriana; Yannibelli, Virginia Daniela; Project scheduling: A multi-objective evolutionary algorithm that optimizes the effectiveness of human resources and the project makespan; Taylor & Francis; Engineering Optimization; 45; 1; 4-2012; 45-65
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