Minimización de la penalidad generada por los retrasos en la entrega de proyectos mediante un modelo de programación lineal entera

Arce, Nilthon; Quiroz, Walter; Gutierrez, Flabio; Tinedo, Luis; Piedra, Jose

doi:10.37787/pakamuros-unj.v9i3.222

Cited by 1 publication

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“…The model aims to determine a work plan for the machine that minimizes the total penalty, so the objective function is given by: Finally, we obtained optimization model that minimizes the penalty generated by delays in the delivery of projects operated by a machine (Arce et al, 2021):…”

Section: Substituting the Deviation Variablementioning

confidence: 99%

Optimization Model that Minimizes the Penalty Caused by Delayed Delivery of Construction Projects

Fernandez,

Segura,

Pino

et al. 2023

J. Professional Business Review

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Purpose: This work aims to minimize the penalty generated by delays in delivering construction projects operated by a single machine. Theoretical framework: The fundamental issues to develop this work are optimization and its application to delays in construction projects operated in their initial stage by a single machine. Design/Methodology/Approach: We presented a construction case study, developed an optimization model, implemented a computational optimization tool and obtained the optimal sequence to perform the tasks. Findings: The numerical results demonstrated the model’s usefulness in minimizing the penalty generated by delays in the delivery of projects. Research, practical & social implications: The benefit of this study is to help managers or decision-makers schedule their construction projects with limited resources and deadlines per activity to minimize penalty costs of delay. Originality/Value: Considering that the construction sector generates the largest labor force in Peru, the study has an important social value by providing a tool to improve operations and incentivize construction companies to continue operating. In addition, it provides a substantial basis for future work by applying optimization in a specific area of civil engineering. To our knowledge, no researcher or company in Peru has yet addressed this study.

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Section: Substituting the Deviation Variablementioning

confidence: 99%