Improving harvesting operations in an oil palm plantation

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.