Solving a Many-Objective Crop Rotation Problem with Evolutionary Algorithms
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Date of publishing2021
Type of publicationresearch article
Crop rotation consists of alternating the types of plants grown in the same place in a planned sequence to obtain improved profits and accomplish environmental outcomes. Determining optimal crop rotations is a relevant decision-making problem in agricultural farms. This work presents a seven objective crop rotation problem considering economic, social, and environmental factors and its solution using evolutionary algorithms; to this aim, an initialization procedure and genetic operators are proposed. Five multi- and many-objective evolutionary algorithms were implemented for a given problem instance, and their results were compared. The comparison shows the methods to be used as a tool for improving decision-making in crop rotations. Also, among the compared algorithms, the RVEA obtains the best values for evaluated metrics for the studied instance.