Modelo matemático de otimização multiobjetivo aplicado à integração lavoura-pecuária-floresta - ILPF

• Ano de defesa: 2024
• Autor(a) principal: Costa, Gilson de Souza
• Tipo de documento: Tese
• Tipo de acesso: Acesso aberto
• Idioma: por
• Instituição de defesa: Universidade Federal de Roraima; Brasil; PRPPG - Pró-reitoria de Pesquisa e Pós-Graduação; PRONAT - Programa de Pós-Graduação em Recursos Naturais; UFRR
• Palavras-chave em Português: Modelagem matemática; Gestão rural; Sistema ILPF; Agricultura sustetável; Ferramentas matemáticas; Sistemas de Integração Lavoura-Pecuária-Floresta; Mathematical modeling; Rural Management; ILPF System; Sustainable Agriculture; Mathematical Tools; Crop-Livestock-Forest Integration systems; CNPQ::CIENCIAS AGRARIAS::RECURSOS FLORESTAIS E ENGENHARIA FLORESTAL::MANEJO FLORESTAL
• Link de acesso: http://repositorio.ufrr.br:8080/jspui/handle/prefix/911

This research allows an integrated view in decision-making, considering several factors such as the increase in agricultural production, the proportionality between the emission and sequestration of greenhouse gases, the use of grains in supplementation and the better distribution of employees. The objective of this work is to present a mathematical multi-objective optimization model, where the functions are linear, applied to Crop-Livestock-Forest Integration (ICLF) systems. The aim is to develop a planning model for agricultural and livestock activities, and to measure potential gains through integration between different cultures, which measure economic, environmental and social aspects. Aware of the fundamental need to obtain data to feed the model, alternative work developed by server Amaury Bendahan from Embrapa Roraima was explored. The proposal presented the ability of multi-objective optimization to evaluate and guide rural producers’ decisions in search of sustainability and efficiency in (ICLF) systems. To achieve the goal in a practical way, an applied research approach is updated, considering a case study carried out at Farm São Paulo, Iracema-Roraima. This work highlights the underutilization of optimization in the trained system and presents a model that outlines the best distribution of the area of that farm, in addition to demonstrating how to solve it using Excel Solver. The proposed model serves to assist rural producers in decision-making in the context of the (ICLF) system, which measures economic, environmental and social aspects. As a result, multi-objective optimization emerges as an answer to dealing with these challenges, allowing us to seek solutions that balance the conflicting goals associated with work, livestock and the forest. Although it does not conclusively determine the system’s ideal practices, this study represents a significant advance for rural producers who use it, due to its ability to consider problems with different resource use conflicts.