Modelagem matemática com aplicação de lógica Fuzzy na programação de compras no ramo hospitalar em contexto da pandemia de COVID-19
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Citações na Scopus
Tipo de produção
Trabalho de Conclusão de Curso
Data
2021-12
Autores
Paschoalino, Felipe Augusto
Golpian, Igor Lima
Pereira, Leonardo Bonfante
Fonseca, Tomaso Reinaud
Rocha, Rodrigo Carvalho
Golpian, Igor Lima
Pereira, Leonardo Bonfante
Fonseca, Tomaso Reinaud
Rocha, Rodrigo Carvalho
Orientador
Hortencio, Hanna Pamplona
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Texto completo (DOI)
Palavras-chave
COVID-19,programação linear fuzzy,abastecimento,fuzzy linear programming,suppllies
Resumo
Devido a pandemia de COVID-19, a demanda por procedimentos de hemodiálise cresceu significativamente, dificultando as atividades de planejamento dos hospitais no processo de aquisição de insumos e medicamentos. No presente trabalho será apresentado um método capaz de prever os gastos necessários para atender a previsão de demanda em um renomado hospital de São Paulo. Um modelo matemático de programação linear foi desenvolvido com objetivo de minimizar os custos de aquisição de material considerando restrições de demanda e estoque. Para refletir a oscilação dos preços de materiais hospitalares em períodos nos quais a demanda e o abastecimento dos mercados fornecedores sofrem incertezas será adicionado ao modelo matemático um fator de correção calculado a partir da metodologia Fuzzy. O modelo desenvolvido foi implementado em linguagem de programação Python utilizando o software Gurobi Optimizer e bibliotecas de algoritmos para metodologia Fuzzy. Testes computacionais foram realizados para validação dos resultados obtidos. Observou-se uma variação de 4% em relação ao orçamento previsto pelo modelo e o orçamento executado em 6 meses entre os anos 2020 e 2021. Em conclusão, a equipe de planejamento do hospital será capaz de realizar uma estimativa de custos de aquisição para um determinado período com a segurança de que o valor provisionado será capaz de atender as compras, sem que haja a necessidade de volumes de estoque excessivos, o que ocasiona em altos custos para o hospital.
Owing to the COVID-19 pandemic, the demand for hemodialysis procedures has grown significantly, hampering hospital’s planning activities in the process of purchasing supplies and medicines. In the present study, will be shown a method capable of predicting the necessary expenses to provision the demand forecast in a renowned hospital in São Paulo. A mathematical model of linear programming was developed in order to minimize material acquisition costs considering demand and stock constraints. In order to reflect the fluctuation in the prices of hospital materials in periods in which the demand and supply of the supplying markets are uncertain, a correction factor calculated using the Fuzzy methodology will be added to the mathematical model. The developed model was implemented in Python programming language using the Gurobi Optimizer software and Fuzzy methodology algorithms libraries. Computational tests were performed to validate the results obtained. A 4% variation has been observed in comparison between the budget foreseen by the model and the budget executed in 6 months between the years 2020 and 2021. In conclusion, the hospital's planning team will be able to estimate the acquisition costs for a given period with the certainty that the provisioned amount will be able to attend purchases, without the need for excessive stock volumes, which results in high costs for the hospital.
Owing to the COVID-19 pandemic, the demand for hemodialysis procedures has grown significantly, hampering hospital’s planning activities in the process of purchasing supplies and medicines. In the present study, will be shown a method capable of predicting the necessary expenses to provision the demand forecast in a renowned hospital in São Paulo. A mathematical model of linear programming was developed in order to minimize material acquisition costs considering demand and stock constraints. In order to reflect the fluctuation in the prices of hospital materials in periods in which the demand and supply of the supplying markets are uncertain, a correction factor calculated using the Fuzzy methodology will be added to the mathematical model. The developed model was implemented in Python programming language using the Gurobi Optimizer software and Fuzzy methodology algorithms libraries. Computational tests were performed to validate the results obtained. A 4% variation has been observed in comparison between the budget foreseen by the model and the budget executed in 6 months between the years 2020 and 2021. In conclusion, the hospital's planning team will be able to estimate the acquisition costs for a given period with the certainty that the provisioned amount will be able to attend purchases, without the need for excessive stock volumes, which results in high costs for the hospital.