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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 |