Decomposition-based heuristic for the zoning and crop planning problem with adjacency constraints

This paper tackles management zone delineation and crop planning problems in an integrated precision agriculture framework. The zoning problem defines relatively homogeneous management zones regarding their soil properties, and for which specific rates of agricultural inputs are necessary. From a su...

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Veröffentlicht in:TOP Jg. 29; H. 1; S. 248 - 265
Hauptverfasser: Albornoz, Víctor M., Zamora, Gabriel E.
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Berlin/Heidelberg Springer Berlin Heidelberg 01.04.2021
Springer Nature B.V
Schlagworte:
Algorithms
Business and Management
Computer models
Constraint modelling
Decomposition
Economic Theory/Quantitative Economics/Mathematical Methods
Economics
Finance
Heuristic
Homogeneity
Industrial and Production Engineering
Insurance
Management
Operations Research/Decision Theory
Optimization
Original Paper
Planning
Programming languages
Soil properties
Statistics for Business
Zoning
90C10
Column generation
Management zones
Column-dependent rows
Crop planning
90C90
49M27
90B50
Binary integer programming
ISSN:1134-5764, 1863-8279
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Zusammenfassung:This paper tackles management zone delineation and crop planning problems in an integrated precision agriculture framework. The zoning problem defines relatively homogeneous management zones regarding their soil properties, and for which specific rates of agricultural inputs are necessary. From a sustainable point of view, the crop planning problem considers cropping of species from different botanic families in adjacent zones at the same time. With this in mind, we propose a novel linear binary integer program for an integrated zoning and crop planning problem with adjacency constraints. In this model, we maximize the incomes of the crop plan subject to zoning constraints and adjacency constraints on crop families. The proposed model has a column-based formulation, and as such, we develop a decomposition-based heuristic which make use of the column generation method with column-dependent rows. The decomposition strategy involves a master problem that deals with ensuring homogeneity of the selected management zones within the field partition and ensuring that the crop plan meets adjacency policies. On the other hand, the pricing problem generates rectangular management zones whose incorporation improves the objective value of the master problem. The algorithm is implemented in JuMP, a modeling language for mathematical optimization embedded in Julia. Results from a set of instances show the relevance of the decomposition-based heuristic.
Bibliographie:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
ISSN:1134-5764
1863-8279
DOI:10.1007/s11750-020-00580-z