Optimization of the harvest planning in the olive oil production: A case study in Chile

03/17/2020
by   Francisco Pérez-Galarce, et al.
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In this work, a mathematical programming model for aiding the decision-making process of olive harvest planning is proposed. The model aims at finding a harvest schedule of different land units that maximizes the total amount of the oil extracted in the mill. Such a harvest plan must ensure quality standards, respect technological limitations, coordinate operations between the field and the mill, and satisfy a budget associated with the harvest operations. Moreover, the presented approach considers the effect of climatological phenomena (rain and frost) during the harvest season, which results in a reduction of olive crops. The model was tested on a real problem of a company located in the central zone of Chile. The experiments with the model show that it is able to obtain better solutions than those obtained by the traditional operation planning when it is tested with real datasets from the company. The optimization model is flexible, allowing the management of several parameters like the project budget and the risks generated by the climate. Thus, it can provide alternative harvest plans in a short time by simulating different climatological scenarios. From a managerial point of view, some lessons about the advantages and difficulties of the model were learned from its use in the company.

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