Fuzzy Optimization Model for Decision-Making in Single Machine Construction Project Planning

Descripción del Articulo

Scheduling for a construction project with a limited number of machines is a critical and well-studied problem. Most studies assume that task processing times are exact; in practice, delays frequently occur, rendering the initial work plan invalid. Therefore, adaptability is crucial to the success o...

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Detalles Bibliográficos
Autor: Arce Fernández,Nilthon
Formato: artículo
Fecha de Publicación:2024
Institución:Universidad Nacional de Jaén
Repositorio:UNJ-Institucional
Lenguaje:inglés
OAI Identifier:oai:repositorio.unj.edu.pe:20.500.14689/1026
Enlace del recurso:http://hdl.handle.net/20.500.14689/1026
https://doi.org/10.3390/math12071088
Nivel de acceso:acceso abierto
Materia:construction project
fuzzy optimization
fuzzy sets
penalties
single-machine task scheduling
decision-making
https://purl.org/pe-repo/ocde/ford#1.01.02
Descripción
Sumario:Scheduling for a construction project with a limited number of machines is a critical and well-studied problem. Most studies assume that task processing times are exact; in practice, delays frequently occur, rendering the initial work plan invalid. Therefore, adaptability is crucial to the success of a project. This work introduces a fuzzy optimization model for the planning of construction projects executed simultaneously and having only one backhoe. The model assumes imprecise task processing times, represented by triangular fuzzy sets, that accept delays up to a permitted degree of tolerance. The model solution obtains a fuzzy work plan. This is a robust plan that supports incidents (delays). A method to apply the model was created. The fuzzy model can help construction companies reduce delays in the delivery of their projects and avoid excessive penalties. The model was implemented in the CPLEX solver, which can quickly obtain an optimal solution for small and medium instances. For large instances, the model must be solved with metaheuristics. This scientific contribution is important for future work since it consists of the application of fuzzy optimization in a specific area of civil engineering.
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