如何利用NSGA-II获得公平的甘蔗收获管理决策

7th International Conference on Hybrid Intelligent Systems (HIS 2007) Pub Date : 2007-09-01 DOI:10.1109/HIS.2007.53

D. Pacheco, T. Lucas, Fernando Buarque de Lima-Neto

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引用次数: 6

摘要

世界对糖的需求，特别是对乙醇等可再生燃料的需求，要求糖厂增加产量。利用人工神经网络(ANN)作为预测核心与NSGA-II算法相关联，旨在帮助决策者优化多目标收获问题。本文介绍了两种方法，并与其他经典方法进行了比较，取得了良好的效果。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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How to Obtain Fair Managerial Decisions in Sugar Cane Harvest Using NSGA-II

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.

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7th International Conference on Hybrid Intelligent Systems (HIS 2007)

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