Multi-stakeholder multi-objective greenhouse design optimization

Xinyuan Min

doi:10.1016/j.agsy.2024.103855

Multi-stakeholder multi-objective greenhouse design optimization

2024-03-01

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DOI：10.1016/j.agsy.2024.103855

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CONTEXT: Optimizing greenhouse design is a complex challenge that involves the large combinational solution space and the interactions between design elements, outdoor climate, and crops. In addition, evaluating greenhouse performance requires consideration of economic and environmental dimensions, as well as different stakeholder priorities. OBJECTIVE: This study aims to identify greenhouse designs that are efficient in terms of economic and environmental performance for both policy makers and investors for four locations in China. METHODS: This paper made a novel combination of operational research methods with bio-economic modelling. Specifically, a bio-economic model was used to simulate the yield, energy use, and economic and environmental performance of different greenhouse designs. A genetic algorithm was used to explore the large solution space to reduce the computational effort. The overall performance of greenhouse design was evaluated using a directional distance function approach, which incorporated stakeholders' priorities for economic and environmental performance through the directional vector. RESULTS AND CONCLUSIONS: The results identify several greenhouse designs that were found to be efficient in terms of economic and environmental performance for both investors and policymakers across various price scenarios. The most influential factors on operating income include the choice of lighting, structure, thermal screen, and CO2 dosing rate. Among lighting options, LED lighting outperforms HPS lighting in terms of both economic and environmental performance. Specifically, incorporating LED lamps with an intensity of 200 mu mol m- 2 s- 1 can increase annual operating income by 97.3 to 200.2 yen m- 2, depending on the region. Conversely, low intensity lighting adversely impacts both economic and environmental performance. A synergistic relationship has been observed between lighting and CO2 dosing. On the other hand, lighting is the primary contributor to greenhouse gas (GHG) emissions. Incorporating LED lighting with an intensity of 200 mu mol m- 2 s- 1 can increase CO2 equivalent emissions from 151.7 to 211.0 kg m- 2. Incorporating thermal screens can effectively reduce GHG emissions. SIGNIFICANCE: The study presents an optimization approach that can be applied to various complex agricultural systems with interactions between many factors and the presence of multiple stakeholders with conflict priorities. In addition, our study has practical implications for the greenhouse sector in China. The wide range of optimal solutions provides policy makers and investors with the flexibility to choose greenhouse designs that meet regional agricultural development goals and budget constraints.

Keywords:

Greenhouse design

Data envelopment analysis

Genetic algorithm

Bio-economic model

Multi-stakeholder multi-objective greenhouse design optimization

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