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dc.contributor.authorFilho, Angelo Aliano
dc.contributor.authorSilva, Helenice Florentino
dc.date.accessioned2022-04-29T08:46:07Z
dc.date.available2022-04-29T08:46:07Z
dc.date.issued2021-01-01
dc.identifierhttp://dx.doi.org/10.1007/978-3-030-85476-8_3
dc.identifier.citationSpringer Proceedings in Mathematics and Statistics, v. 374, p. 25-37.
dc.identifier.issn2194-1017
dc.identifier.issn2194-1009
dc.identifier.urihttp://hdl.handle.net/11449/231558
dc.description.abstractThis study presents a nonlinear bi-objective 0-1 optimization model for sustainable cultivation and proposes an exact method to solve it. In this formulation, among a set of cultures, a predefined number of cultivable plots and planning horizon, it is intended to decide which crops, periods and plots should be cultivated. Two conflicting objectives are considered: (i) minimize the proliferation of pests and (ii) maximize the profit of the planting schedule in all planning horizon. The mathematical formulation was solved by the classical ε- constrained method. We linearized the original model and obtained an alternative linear version of our problem. Then, we compare the performance of ε- constrained method in this two formulation to determine some Pareto optimal solutions in 27 instances generated by a semi-random procedure of real dimension. The experiments showed that mathematical models along with the proposed method may be powerful tools in the complex decision-making in this field.en
dc.format.extent25-37
dc.language.isoeng
dc.relation.ispartofSpringer Proceedings in Mathematics and Statistics
dc.sourceScopus
dc.subjectMulti-objective optimization
dc.subjectSustainability
dc.subjectε- Constrained method
dc.titleThe ε- Constrained Method to Solve a Bi-Objective Problem of Sustainable Cultivationen
dc.typeTrabalho apresentado em evento
dc.contributor.institutionFederal Technological University of Paraná
dc.contributor.institutionUniversidade de São Paulo (USP)
dc.description.affiliationFederal Technological University of Paraná
dc.description.affiliationInstitute of Bioestatistics of Botucatu State University of São Paulo
dc.identifier.doi10.1007/978-3-030-85476-8_3
dc.identifier.scopus2-s2.0-85119892544
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