- -

Forecasting the Project Duration Average and Standard Deviation from Deterministic Schedule Information

RiuNet: Repositorio Institucional de la Universidad Politécnica de Valencia

Compartir/Enviar a

Citas

Estadísticas

  • Estadisticas de Uso

Forecasting the Project Duration Average and Standard Deviation from Deterministic Schedule Information

Mostrar el registro sencillo del ítem

Ficheros en el ítem

dc.contributor.author Ballesteros-Pérez, Pablo es_ES
dc.contributor.author Cerezo-Narváez, Alberto es_ES
dc.contributor.author Otero-Mateo, Manuel es_ES
dc.contributor.author Pastor-Fernández, Andrés es_ES
dc.contributor.author Zhang, Jingxiao es_ES
dc.contributor.author Vanhoucke, Mario es_ES
dc.date.accessioned 2023-06-30T18:01:01Z
dc.date.available 2023-06-30T18:01:01Z
dc.date.issued 2020-01-16 es_ES
dc.identifier.uri http://hdl.handle.net/10251/194602
dc.description.abstract [EN] Most construction managers use deterministic scheduling techniques to plan construction projects and estimate their duration. However, deterministic techniques are known to underestimate the project duration. Alternative methods, such as Stochastic Network Analysis, have rarely been adopted in practical contexts as they are commonly computer-intensive, require extensive historical information, have limited contextual/local validity and/or require skills most practitioners have not been trained for. In this paper, we propose some mathematical expressions to approximate the average and the standard deviation of a project duration from basic deterministic schedule information. The expressions¿ performance is successfully tested in a 4100-network dataset with varied activity durations and activity durations variability. Calculations are quite straightforward and can be implemented manually. Furthermore, unlike the Project Evaluation and Review Technique (PERT), they allow drawing inferences about the probability of project duration in the presence of several critical and subcritical paths with minimal additional calculation. es_ES
dc.description.sponsorship The first author acknowledges the Spanish Ministry of Science, Innovation, and Universities for his Ramon y Cajal contract (RYC-2017-22222) co-funded by the European Social Fund. The first two authors also acknowledge the help received by the research project PIN-0053-2019 funded by the Fundación Pública Andaluza Progreso y Salud (Junta de Andalucía, Spain). The first four authors also acknowledge the help received by the research group TEP-955 from the PAIDI (Junta de Andalucía, Spain). Finally, the fifth author, acknowledges the support from the National Natural Science Foundation of China (No. 71301013), the National Social Science Fund Post-financing projects (No.19FJYB017), the List of Key Science and Technology Projects in China¿s Transportation Industry in 2018-International Science and Technology Cooperation Project (No.2018-GH-006), and the Humanity and Social Science Program Foundation of the Ministry of Education of China (No. 17YJA790091). es_ES
dc.language Inglés es_ES
dc.publisher MDPI AG es_ES
dc.relation.ispartof Applied Sciences es_ES
dc.rights Reconocimiento (by) es_ES
dc.subject Project duration es_ES
dc.subject Scheduling es_ES
dc.subject Merge event bias es_ES
dc.subject Construction es_ES
dc.subject PERT es_ES
dc.subject.classification PROYECTOS DE INGENIERIA es_ES
dc.title Forecasting the Project Duration Average and Standard Deviation from Deterministic Schedule Information es_ES
dc.type Artículo es_ES
dc.identifier.doi 10.3390/app10020654 es_ES
dc.relation.projectID info:eu-repo/grantAgreement/NSFC//71301013/ es_ES
dc.relation.projectID info:eu-repo/grantAgreement/MCIU//RYC-2017-22222//AYUDAS RAMON Y CAJAL/ es_ES
dc.relation.projectID info:eu-repo/grantAgreement/MOST//2018-GH-006/ es_ES
dc.relation.projectID info:eu-repo/grantAgreement/MOE//17YJA790091/ es_ES
dc.relation.projectID info:eu-repo/grantAgreement/NSSFC//19FJYB017/ es_ES
dc.rights.accessRights Abierto es_ES
dc.contributor.affiliation Universitat Politècnica de València. Escuela Técnica Superior de Ingenieros Industriales - Escola Tècnica Superior d'Enginyers Industrials es_ES
dc.description.bibliographicCitation Ballesteros-Pérez, P.; Cerezo-Narváez, A.; Otero-Mateo, M.; Pastor-Fernández, A.; Zhang, J.; Vanhoucke, M. (2020). Forecasting the Project Duration Average and Standard Deviation from Deterministic Schedule Information. Applied Sciences. 10(2):1-22. https://doi.org/10.3390/app10020654 es_ES
dc.description.accrualMethod S es_ES
dc.relation.publisherversion https://doi.org/10.3390/app10020654 es_ES
dc.description.upvformatpinicio 1 es_ES
dc.description.upvformatpfin 22 es_ES
dc.type.version info:eu-repo/semantics/publishedVersion es_ES
dc.description.volume 10 es_ES
dc.description.issue 2 es_ES
dc.identifier.eissn 2076-3417 es_ES
dc.relation.pasarela S\443149 es_ES
dc.contributor.funder Ministry of Education of China es_ES
dc.contributor.funder National Social Science Fund of China es_ES
dc.contributor.funder Ministry of Science and Technology, China es_ES
dc.contributor.funder National Natural Science Foundation of China es_ES
dc.contributor.funder Fundación Pública Andaluza Progreso y Salud es_ES
dc.contributor.funder Ministerio de Ciencia, Innovación y Universidades es_ES


Este ítem aparece en la(s) siguiente(s) colección(ones)

Mostrar el registro sencillo del ítem