Title :
How to Obtain Fair Managerial Decisions in Sugar Cane Harvest Using NSGA-II
Author :
Pacheco, Diogo Ferreira ; Lucas, Tarcísio Daniel P ; De Lima Neto, Fernando B.
Author_Institution :
Pernambuco State Univ., Recife
Abstract :
The world´s demand for sugar and particularly for renewable fuels such as ethanol requires an increase in production in sugar mills. The use of artificial neural networks (ANN) posed as a predictive core associated with the algorithm NSGA-II aims at helping decision makers to optimize the multi-objective harvest problem. This paper presents two approaches and the good results achieved as compared with other classical techniques.
Keywords :
agriculture; decision making; neural nets; sugar; artificial neural networks; ethanol; fair managerial decisions; multiobjective harvest problem; renewable fuels; sugar cane harvest; sugar mills; Artificial neural networks; Ethanol; Fuels; Global warming; Milling machines; Petroleum; Pollution; Production; Productivity; Sugar industry;
Conference_Titel :
Hybrid Intelligent Systems, 2007. HIS 2007. 7th International Conference on
Conference_Location :
Kaiserlautern
Print_ISBN :
978-0-7695-2946-2
DOI :
10.1109/HIS.2007.53
