dc.contributorUniversidade Estadual Paulista (Unesp)
dc.contributorUniversidade de Lisboa
dc.date.accessioned2016-04-01T18:44:28Z
dc.date.available2016-04-01T18:44:28Z
dc.date.created2016-04-01T18:44:28Z
dc.date.issued2014
dc.identifierInternational Journal of Metaheuristics, v. 3, n. 3, p. 199-222, 2014.
dc.identifier1755-2176
dc.identifierhttp://hdl.handle.net/11449/137165
dc.identifier10.1504/ijmheur.2014.065169
dc.identifier9853363280628232
dc.description.abstractThis paper presents a mathematical model adapted from literature for the crop rotation problem with demand constraints (CRP-D). The main aim of the present work is to study metaheuristics and their performance in a real context. The proposed algorithms for solution of the CRP-D are a genetic algorithm, a simulated annealing and hybrid approaches: a genetic algorithm with simulated annealing and a genetic algorithm with local search algorithm. A new constructive heuristic was also developed to provide initial solutions for the metaheuristics. Computational experiments were performed using a real planting area and semi-randomly generated instances created by varying the number, positions and dimensions of the lots. The computational results showed that these algorithms determined good feasible solutions in a short computing time as compared with the time spent to get optimal solutions, thus proving their efficacy for dealing with this practical application of the CRP-D.
dc.languageeng
dc.relationInternational Journal of Metaheuristics
dc.rightsAcesso restrito
dc.sourceCurrículo Lattes
dc.subjectOptimisation
dc.subjectMetaheuristics
dc.subjectCrop rotation
dc.subjectMathematical modelling
dc.subjectGenetic algorithms
dc.subjectSimulated annealing
dc.titleMetaheuristics for a crop rotation problem
dc.typeArtículos de revistas


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