Perfeccionamiento del modelo de Adoma mediante la inclusión de la ambigüedad en algunos de sus parámetros
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Date
2004
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Universidad de Concepción
Abstract
En la presente investigación se perfeccionó el modelo “ADOMA”, Administración de Operaciones de Maquinaria Agrícola, mediante la inclusión de las pérdidas económicas por retraso en la ejecución de las labores, además se incorporó la incertidumbre asociada a estas pérdidas utilizando Lógica Difusa. Para tal fin, se elaboró un sistema de soporte de toma de decisiones que apoya la programación de las labores y la asignación de las máquinas basado en lógica difusa, llamado SSDLD (Sistema de Soporte de Decisión con Lógica Difusa).
Se recopiló información de pérdidas por retraso en cuatro cultivos frecuentes en la 8ª Región de Chile, los valores de pérdida fueron convertidos en valores difusos con tres niveles lingüísticos: Bajo, Medio y Alto y representados por números difusos trapezoidales. Posteriormente, los números difusos fueron ordenados, para así establecer la prioridad en la ejecución de las labores y la asignación de máquinas. Para validar el modelo se elaboró un escenario con cultivos con información de pérdida económica y dos cultivos sin información, los datos fueron introducidos en el modeloADOMA y en el modelo ADOMA con SSDLD.
In this research work the "ADOMA" model, (Agricultural Machinery Operations Management) was improved, by including the economic losses due to tardiness in the operations execution, in addition, the uncertainty associated to economic losses was incorporated by using fuzzy logic. To such end a decision-making support system was created in order to decide the operations scheduling and the assignment of the machines based on fuzzy logic, called DSSFL (Decision Support System with Fuzzy Logic). The information about economic losses for tardiness of four common crops in the 8th region of Chile was compiled. The values of losses were converted in fuzzy values, with three linguistic levels: low, medium and high and represented by fuzzy trapezoidal numbers. Subsequently, the fuzzy numbers were ranked in order to assess the priority in the execution of the operations and the assignment of machines. To validate the model a stage was elaborated with crops for which information related to economic losses were available and with two crops without this type of information. The data were introduced in both models ADOMA and ADOMA FLDSS. Three algorithms were designed. One to generate the function of membership of the losses in the tardiness operations, another to create the fuzzy number that represents the fuzzified quantity of the loss and a last algorithm, to establish the ranking fuzzy numbers of the losses. The results indicate that the obtained scheduling adjusts better to the requests of a stage with multiple crops, keeping in mind the economic losses for tardiness, privileging those crops of greater economic importance to the farmer. The heuristic-fuzzy model is a valuable tool to achieve efficient use of the agricultural machinery and will back up the decision-making process under uncertainty.
In this research work the "ADOMA" model, (Agricultural Machinery Operations Management) was improved, by including the economic losses due to tardiness in the operations execution, in addition, the uncertainty associated to economic losses was incorporated by using fuzzy logic. To such end a decision-making support system was created in order to decide the operations scheduling and the assignment of the machines based on fuzzy logic, called DSSFL (Decision Support System with Fuzzy Logic). The information about economic losses for tardiness of four common crops in the 8th region of Chile was compiled. The values of losses were converted in fuzzy values, with three linguistic levels: low, medium and high and represented by fuzzy trapezoidal numbers. Subsequently, the fuzzy numbers were ranked in order to assess the priority in the execution of the operations and the assignment of machines. To validate the model a stage was elaborated with crops for which information related to economic losses were available and with two crops without this type of information. The data were introduced in both models ADOMA and ADOMA FLDSS. Three algorithms were designed. One to generate the function of membership of the losses in the tardiness operations, another to create the fuzzy number that represents the fuzzified quantity of the loss and a last algorithm, to establish the ranking fuzzy numbers of the losses. The results indicate that the obtained scheduling adjusts better to the requests of a stage with multiple crops, keeping in mind the economic losses for tardiness, privileging those crops of greater economic importance to the farmer. The heuristic-fuzzy model is a valuable tool to achieve efficient use of the agricultural machinery and will back up the decision-making process under uncertainty.
Description
Tesis presentada para optar al grado de Magíster en Ingeniería Agrícola con mención en Mecanización y Energía
Keywords
Maquinaria agrícola - Chile, Mecanización agrícola - Chile, Sistema de Administración de Maquinaria Agrícola