Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
480869 | European Journal of Operational Research | 2010 | 8 Pages |
Abstract
Optimization models are increasingly being used in agricultural planning. However, the inherent uncertainties present in agriculture make it difficult. In recent years, robust optimization has emerged as a methodology that allows dealing with uncertainty in optimization models, even when probabilistic knowledge of the phenomenon is incomplete. In this paper, we consider a wine grape harvesting scheduling optimization problem subject to several uncertainties, such as the actual productivity that can be achieved when harvesting. We study how effective robust optimization is solving this problem in practice. We develop alternative robust models and show results for some test problems obtained from actual wine industry problems.
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Physical Sciences and Engineering
Computer Science
Computer Science (General)
Authors
Carlos Bohle, Sergio Maturana, Jorge Vera,