TY - JOUR
T1 - Energy-efficient automated vertical farms
AU - Delorme, Maxence
AU - Santini, Alberto
N1 - Funding Information:
The authors would like to thank the two anonymous reviewers for their valuable comments that have helped to improve the presentation of this paper. Alberto Santini was partially funded by: MICINN (Spain) through the programme Juan de la Cierva Formacin; AEI (Spain) and the Barcelona Graduate School of Economics (Spain) through Severo Ochoa grant CEX2019-000915-S; the European Union's Horizon 2020 research and innovation programme under a Marie Skodowska-Curie grant (EUTOPIA Cofund); ESSEC Business School (France) through the Visiting Professor programme.
Funding Information:
The authors would like to thank the two anonymous reviewers for their valuable comments that have helped to improve the presentation of this paper. Alberto Santini was partially funded by: MICINN (Spain) through the programme Juan de la Cierva Formacin; AEI (Spain) and the Barcelona Graduate School of Economics (Spain) through Severo Ochoa grant CEX2019-000915-S; the European Union’s Horizon 2020 research and innovation programme under a Marie Skodowska-Curie grant (EUTOPIA Cofund); ESSEC Business School (France) through the Visiting Professor programme.
Publisher Copyright:
© 2022 The Author(s)
PY - 2022/6
Y1 - 2022/6
N2 - Autonomous vertical farms (VFs) are becoming increasingly more popular because they allow to grow food minimising water consumption and the use of pesticides, while greatly increasing the yield per square metre compared with traditional agriculture. To meet sustainability goals, however, VFs must operate at maximum efficiency; it would be otherwise impossible to compete with the energy source powering plant growth in traditional agriculture: the sun. We introduce the Vertical Farming Elevator Energy Minimisation Problem (VFEEMP), which arises when minimising the energy consumption of automatic elevators servicing VFs. We prove that the decision problem associated with the VFEEMP is NP-complete. To solve the problem, we propose three Mixed-Integer Linear Programming (MIP) formulations together with valid inequalities, and a Constraint Programming model. We present a large set of instances, both synthetic and derived from real-life data, and we determine through extensive computational experiments which instance characteristics have an impact on the difficulty of the problem and which formulations are the most suitable to solve the VFEEMP.
AB - Autonomous vertical farms (VFs) are becoming increasingly more popular because they allow to grow food minimising water consumption and the use of pesticides, while greatly increasing the yield per square metre compared with traditional agriculture. To meet sustainability goals, however, VFs must operate at maximum efficiency; it would be otherwise impossible to compete with the energy source powering plant growth in traditional agriculture: the sun. We introduce the Vertical Farming Elevator Energy Minimisation Problem (VFEEMP), which arises when minimising the energy consumption of automatic elevators servicing VFs. We prove that the decision problem associated with the VFEEMP is NP-complete. To solve the problem, we propose three Mixed-Integer Linear Programming (MIP) formulations together with valid inequalities, and a Constraint Programming model. We present a large set of instances, both synthetic and derived from real-life data, and we determine through extensive computational experiments which instance characteristics have an impact on the difficulty of the problem and which formulations are the most suitable to solve the VFEEMP.
KW - Constraint programming
KW - Integer linear programming
KW - Operational research applications
KW - Task scheduling
KW - Vertical farming
U2 - 10.1016/j.omega.2022.102611
DO - 10.1016/j.omega.2022.102611
M3 - Article
AN - SCOPUS:85124211951
SN - 0305-0483
VL - 109
JO - Omega-International Journal of Management Science
JF - Omega-International Journal of Management Science
M1 - 102611
ER -