dc.contributor | Universidade Estadual Paulista (Unesp) | |
dc.contributor | Universidade de Lisboa | |
dc.date.accessioned | 2016-04-01T18:44:28Z | |
dc.date.available | 2016-04-01T18:44:28Z | |
dc.date.created | 2016-04-01T18:44:28Z | |
dc.date.issued | 2014 | |
dc.identifier | International Journal of Metaheuristics, v. 3, n. 3, p. 199-222, 2014. | |
dc.identifier | 1755-2176 | |
dc.identifier | http://hdl.handle.net/11449/137165 | |
dc.identifier | 10.1504/ijmheur.2014.065169 | |
dc.identifier | 9853363280628232 | |
dc.description.abstract | This 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.language | eng | |
dc.relation | International Journal of Metaheuristics | |
dc.rights | Acesso restrito | |
dc.source | Currículo Lattes | |
dc.subject | Optimisation | |
dc.subject | Metaheuristics | |
dc.subject | Crop rotation | |
dc.subject | Mathematical modelling | |
dc.subject | Genetic algorithms | |
dc.subject | Simulated annealing | |
dc.title | Metaheuristics for a crop rotation problem | |
dc.type | Artículos de revistas | |