Fuzzy Optimization Model for Decision-Making in Single Machine Construction Project Planning
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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| Format: | Article |
| Language: | English |
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MDPI AG
2024-04-01
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| Series: | Mathematics |
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| Online Access: | https://www.mdpi.com/2227-7390/12/7/1088 |
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| author | Nilthon Arce Fernández Flabio Gutiérrez Segura Manuel Emilio Milla Pino Jose Manuel Palomino Ojeda Alfredo Lázaro Ludeña Gutiérrez River Chávez Santos |
| author_facet | Nilthon Arce Fernández Flabio Gutiérrez Segura Manuel Emilio Milla Pino Jose Manuel Palomino Ojeda Alfredo Lázaro Ludeña Gutiérrez River Chávez Santos |
| author_sort | Nilthon Arce Fernández |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-04-24T10:38:50Z |
| format | Article |
| id | doaj.art-2968bc71220549518fcd94224c57e571 |
| institution | Directory Open Access Journal |
| issn | 2227-7390 |
| language | English |
| last_indexed | 2024-04-24T10:38:50Z |
| publishDate | 2024-04-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Mathematics |
| spelling | doaj.art-2968bc71220549518fcd94224c57e5712024-04-12T13:22:51ZengMDPI AGMathematics2227-73902024-04-01127108810.3390/math12071088Fuzzy Optimization Model for Decision-Making in Single Machine Construction Project PlanningNilthon Arce Fernández0Flabio Gutiérrez Segura1Manuel Emilio Milla Pino2Jose Manuel Palomino Ojeda3Alfredo Lázaro Ludeña Gutiérrez4River Chávez Santos5Academic Department of Basic and Applied Sciences, Universidad Nacional de Jaén, Jaén 06800, PeruMathematics Department, Faculty of Science, Universidad Nacional de Piura, Castilla, Piura 20002, PeruDepartment of Civil Engineering, Faculty of Engineering, Universidad Nacional de Jaén, Jaén 06800, PeruData Science Research Institute, Universidad Nacional de Jaén, Jaén 06800, PeruResearch Office, Universidad Nacional de Jaén, Jaén 06800, PeruAcademic Department of Education, Communication Sciences and Basic Sciences, Faculty of Education and Communication Sciences, Universidad Nacional Toribio Rodríguez de Mendoza de Amazonas, Chachapoyas 01001, PeruScheduling 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.https://www.mdpi.com/2227-7390/12/7/1088construction projectfuzzy optimizationfuzzy setspenaltiessingle-machine task schedulingdecision-making |
| spellingShingle | Nilthon Arce Fernández Flabio Gutiérrez Segura Manuel Emilio Milla Pino Jose Manuel Palomino Ojeda Alfredo Lázaro Ludeña Gutiérrez River Chávez Santos Fuzzy Optimization Model for Decision-Making in Single Machine Construction Project Planning Mathematics construction project fuzzy optimization fuzzy sets penalties single-machine task scheduling decision-making |
| title | Fuzzy Optimization Model for Decision-Making in Single Machine Construction Project Planning |
| title_full | Fuzzy Optimization Model for Decision-Making in Single Machine Construction Project Planning |
| title_fullStr | Fuzzy Optimization Model for Decision-Making in Single Machine Construction Project Planning |
| title_full_unstemmed | Fuzzy Optimization Model for Decision-Making in Single Machine Construction Project Planning |
| title_short | Fuzzy Optimization Model for Decision-Making in Single Machine Construction Project Planning |
| title_sort | fuzzy optimization model for decision making in single machine construction project planning |
| topic | construction project fuzzy optimization fuzzy sets penalties single-machine task scheduling decision-making |
| url | https://www.mdpi.com/2227-7390/12/7/1088 |
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