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Advanced Computational Methods for Agriculture Machinery Movement Optimization with Applications in Sugarcane Production

Martin Filip, Tomáš Zoubek, Roman Bumbálek, Pavel Černý, Carlos Eduardo de Araújo Batista, Pavel Olšan, Petr Bartoš, Pavel Kříž, Maohua Xiao, Antonín Dolan, Pavol Findura

2020Agriculture38 citationsDOIOpen Access PDF

Abstract

This paper considers the evolution of processes applied in agriculture for field operations developed from non-organized handmade activities into very specialized and organized production processes. A set of new approaches based on the application of metaheuristic optimization methods and smart automatization known as Agriculture 4.0 has enabled a rapid increase in in-field operations’ productivity and offered unprecedented economic benefits. The aim of this paper is to review modern approaches to agriculture machinery movement optimization with applications in sugarcane production. Approaches based on algorithms for the division of spatial configuration, route planning or path planning, as well as approaches using cost parameters, e.g., energy, fuel and time consumption, are presented. The combination of algorithmic and economic methodologies including evaluation of the savings and investments and their cost/benefit relation is discussed.

Topics & Concepts

AgricultureProduction (economics)ProductivityComputer scienceMetaheuristicField (mathematics)Precision agricultureAgricultural engineeringOperations researchIndustrial engineeringEngineeringEconomicsArtificial intelligenceMathematicsEcologyPure mathematicsBiologyMacroeconomicsBiofuel production and bioconversionAgricultural Engineering and MechanizationAdvanced Manufacturing and Logistics Optimization