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

Martin Filip, Tomas Zoubek, Roman Bumbalek, Pavel Cerny, Carlos E. Batista, Pavel Olsan, Petr Bartos, Pavel Kriz, Maohua Xiao, Antonin Dolan and Pavol Findura
Additional contact information
Martin Filip: Faculty of Agriculture, University of South Bohemia, Studentska 1668, 370 05 Ceske Budejovice, Czech Republic
Tomas Zoubek: Faculty of Agriculture, University of South Bohemia, Studentska 1668, 370 05 Ceske Budejovice, Czech Republic
Roman Bumbalek: Faculty of Agriculture, University of South Bohemia, Studentska 1668, 370 05 Ceske Budejovice, Czech Republic
Pavel Cerny: Faculty of Education, University of South Bohemia, Jeronymova 10, 371 15 Ceske Budejovice, Czech Republic
Carlos E. Batista: Faculty of Engineering of Ilha Solteira (FEIS/UNESP), São Paulo State University, Passeio Monção 830, 15385-000 Ilha Solteira, Brazil
Pavel Olsan: Faculty of Agriculture, University of South Bohemia, Studentska 1668, 370 05 Ceske Budejovice, Czech Republic
Petr Bartos: Faculty of Agriculture, University of South Bohemia, Studentska 1668, 370 05 Ceske Budejovice, Czech Republic
Pavel Kriz: Faculty of Agriculture, University of South Bohemia, Studentska 1668, 370 05 Ceske Budejovice, Czech Republic
Maohua Xiao: College of Engineering, Nanjing Agriculture University, Nanjing 210031, China
Antonin Dolan: Faculty of Agriculture, University of South Bohemia, Studentska 1668, 370 05 Ceske Budejovice, Czech Republic
Pavol Findura: Faculty of Agriculture, University of South Bohemia, Studentska 1668, 370 05 Ceske Budejovice, Czech Republic

Agriculture, 2020, vol. 10, issue 10, 1-20

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.

Keywords: optimization; agricultural machinery; metaheuristic algorithm; precision agriculture; route planning (search for similar items in EconPapers)
JEL-codes: Q1 Q10 Q11 Q12 Q13 Q14 Q15 Q16 Q17 Q18 (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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Persistent link: https://EconPapers.repec.org/RePEc:gam:jagris:v:10:y:2020:i:10:p:434-:d:420187

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