Improving harvesting operations in an oil palm plantation

Mariana Escallón-Barrios (), Daniel Castillo-Gomez (), Jorge Leal (), Carlos Montenegro () and Andrés L. Medaglia ()
Additional contact information
Mariana Escallón-Barrios: Universidad de Los Andes
Daniel Castillo-Gomez: Universidad de Los Andes
Jorge Leal: Universidad de Los Andes
Carlos Montenegro: Universidad de Los Andes
Andrés L. Medaglia: Universidad de Los Andes

Annals of Operations Research, 2022, vol. 314, issue 2, No 6, 449 pages

Abstract: Abstract Oil palm agricultural systems involve large extensions of land that demand careful planning of the harvesting operations. The plantation manager is in charge of synchronizing resources (i.e., crews and a complex cableway network) to harvest at the right time to maximize palm oil yield in latter stages of the value chain. In particular, in this type of crop it is ideal to visit each palm every eight to twelve days to avoid loose fruit picking, over-ripeness, or rotten fruit harvesting. To optimize harvest operations, we propose an end-to-end analytics solution involving data treatment, descriptive (simulation), and prescriptive models (optimization) in this agricultural system. At the core of our approach lies a set of interconnected models that use optimization, heuristic techniques, and simulation. These models cover strategic (harvest cycle), tactical (resource allocation), and operational (transport allocation) decisions. We present a case study of a 2000-ha plantation located in the Colombian Orinoquia. The results show a strong potential for improving yield by reducing the harvest cycle length from 19.6 to 8.3 days.

Keywords: Column generation; Scheduling; Discrete event simulation; Agricultural systems; Operations research in agriculture (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
http://link.springer.com/10.1007/s10479-020-03686-6 Abstract (text/html)
Access to the full text of the articles in this series is restricted.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:annopr:v:314:y:2022:i:2:d:10.1007_s10479-020-03686-6

Ordering information: This journal article can be ordered from
http://www.springer.com/journal/10479

DOI: 10.1007/s10479-020-03686-6

Access Statistics for this article

Annals of Operations Research is currently edited by Endre Boros

More articles in Annals of Operations Research from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().