4.7 Article

Energy-efficient automated vertical farms

出版社

PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.omega.2022.102611

关键词

Vertical farming; Task scheduling; Operational research applications; Integer linear programming; Constraint programming

资金

  1. MICINN (Spain)
  2. AEI (Spain)
  3. Barcelona Graduate School of Economics (Spain) [CEX2019-000915-S]
  4. European Union
  5. ESSEC Business School (France)

向作者/读者索取更多资源

Autonomous vertical farms are gaining popularity due to their ability to minimize water consumption and pesticide use while increasing yield per square meter. However, in order to meet sustainability goals, these farms must operate efficiently to compete with traditional agriculture powered by solar energy. This study focuses on the energy consumption of automatic elevators in vertical farms and presents various models and computational experiments to tackle the problem.
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 pow-ering 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 N P-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. (c) 2022 The Author(s). Published by Elsevier Ltd. This is an open access article under the CC BY license ( http://creativecommons.org/licenses/by/4.0/ )

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