TY - GEN
T1 - Embedding a Long Short-Term Memory Network in a Constraint Programming Framework for Tomato Greenhouse Optimisation
AU - van Bokkem, Dirk
AU - van den Hemel, Max
AU - Dumančić, Sebastijan
AU - Yorke-Smith, Neil
PY - 2023
Y1 - 2023
N2 - Increasing global food demand, accompanied by the limited number of expert growers, brings the need for more sustainable and efficient horticulture. The controlled environment of greenhouses enable data collection and precise control. For optimally controlling the greenhouse climate, a grower not only looks at crop production, but rather aims at maximising the profit. However this is a complex, long term optimisation task. In this paper, Constraint Programming (CP) is applied to task of optimal greenhouse economic control, by leveraging a learned greenhouse climate model through a CP embedding. In collaboration with an industrial partner, we demonstrate how to model the greenhouse climate with an LSTM model, embed this LSTM into a CP optimisation framework, and optimise the expected profit of the grower. This data-to-decision pipeline is being integrated into a decision support system for multiple greenhouses in the Netherlands.
AB - Increasing global food demand, accompanied by the limited number of expert growers, brings the need for more sustainable and efficient horticulture. The controlled environment of greenhouses enable data collection and precise control. For optimally controlling the greenhouse climate, a grower not only looks at crop production, but rather aims at maximising the profit. However this is a complex, long term optimisation task. In this paper, Constraint Programming (CP) is applied to task of optimal greenhouse economic control, by leveraging a learned greenhouse climate model through a CP embedding. In collaboration with an industrial partner, we demonstrate how to model the greenhouse climate with an LSTM model, embed this LSTM into a CP optimisation framework, and optimise the expected profit of the grower. This data-to-decision pipeline is being integrated into a decision support system for multiple greenhouses in the Netherlands.
UR - http://www.scopus.com/inward/record.url?scp=85168254857&partnerID=8YFLogxK
U2 - 10.1609/aaai.v37i13.26867
DO - 10.1609/aaai.v37i13.26867
M3 - Conference contribution
AN - SCOPUS:85168254857
T3 - Proceedings of the 37th AAAI Conference on Artificial Intelligence, AAAI 2023
SP - 15731
EP - 15737
BT - AAAI-23 Special Programs, IAAI-23, EAAI-23, Student Papers and Demonstrations
A2 - Williams, Brian
A2 - Chen, Yiling
A2 - Neville, Jennifer
PB - American Association for Artificial Intelligence (AAAI)
T2 - 37th AAAI Conference on Artificial Intelligence, AAAI 2023
Y2 - 7 February 2023 through 14 February 2023
ER -
