This paper addresses the management of a sugarcane harvest over a multi-year planning period. A methodology to assist the harvest planning of the sugarcane is proposed in order to improve the production of POL (a measure of the amount of sucrose contained in a sugar solution) and the quality of the raw material, considering the constraints imposed by the mill such as the demand per period. An extended goal programming model is proposed for optimizing the harvest plan of the sugarcane so the harvesting point is as close as possible to the ideal, considering the constrained nature of the problem. A genetic algorithm (GA) is developed to tackle the problem in order to solve realistically large problems within an appropriate computational time. A comparative analysis between the GA and an exact method for small instances is also given in order to validate the performance of the developed model and methods. Computational results for medium and large farm instances using GA are also presented in order to demonstrate the capability of the developed method. The computational results illustrate the trade-off between satisfying the conflicting goals of harvesting as closely as possible to the ideal and making optimum use of harvesting equipment with a minimum of movement between farms. They also demonstrate that, whilst harvesting plans for small scale farms can be generated by the exact method, a meta-heuristic GA method is currently required in order to devise plans for medium and large farms.

Anaerobic digesters have been highlighted due to the current energy crisis and its consequent search for alternative energy sources, allied to the intense process of livestock farming and agriculture modernization, which besides demanding a lot of energy, produces a great amount of crop and animal residues, most of the times generating sanitary problems. The aim of this work is to provide a mathematical tool to establish parameters for projects of construction of rural digesters, considering the response to energy demand, the suitability of the dimensions of the systems, yield factors and the guarantee of functionality. Non-linear optimization models, of easy resolution, for the three main types of rural digesters were formulated in this way. With the resolution of these models one can determine the height and the diameter that lead to a minimum volume for each type, so reducing the necessary amount of masonry and, consequently, diminishing the cost. Key words: mathematical model, optimization, parameters for designing FERRAMENTA MATEMÁTICA PARA AUXÍLIO NO DIMENSIONAMENTO DE BIODIGESTORES RURAISRESUMO: Os biodigestores têm sido objetos de grande destaque devido a atual crise de energia e conseqüente busca de fontes alternativas. Outro fator que coloca os biodigestores em evidência é o intenso processo de modernização da agropecuária, que além da grande demanda de energia, produz um volume de resíduos animais e de culturas, que ocasiona muitas vezes problemas de ordem sanitária. O objetivo deste trabalho é fornecer uma ferramenta matemática para determinação de parâmetros para projetos de construção de biodigestores rurais, levando-se em consideração o atendimento de necessidades energéticas, obedecendo os dimensionamentos dos sistemas, fatores de rendimento e garantindo a funcionalidade. Para isto, foram formulados modelos de otimização não lineares, de fácil resolução, para os três principais tipos de biodigestores rurais. Com a resolução destes modelos são determinados a altura e o diâmetro que levem a um volume mínimo para cada tipo, com isto reduz-se a quantidade necessária de materiais de alvenaria e consequentemente o custo do biodigestor é diminuído. Palavras-chave: modelo matemático, otimização, parâmetros de projeto

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