AGRICULTURAL INNOVATION
A robust decision framework for vertical farming using integrated objective weighting and distance driven ranking approach
This study provides a comprehensive analysis of Vertical Farming Techniques (VFTs) including hydroponics, aquaponics, aeroponics, and fogponics. It introduces a novel hybrid Logarithmic Percentage Change-driven Objective Weighting-Multi-attributive Border Approximation Area Comparison framework for objective analysis and optimal technology selection, concluding that aquaponics is the ideal VFT method due to high production yield, followed by aeroponics, fogponics, and hydroponics. The framework's reliability is validated through comparison and sensitivity analysis.
Executive Impact
This research offers crucial insights for enterprise leaders looking to optimize agricultural practices and drive innovation.
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Reduced Water Consumption
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World's Fresh Water Usage in Agriculture
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Projected Population by 2050
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Aquaponics Ranking for VFT
Deep Analysis & Enterprise Applications
Select a topic to dive deeper, then explore the specific findings from the research, rebuilt as interactive, enterprise-focused modules.
Enterprise Process Flow
Formation of linguistic scale
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Setting up of alternatives & criteria
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Construct individual DMs
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Aggregated DM is formed
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LOPCOW for normalization and weighting
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MABAC for ranking alternatives
Methodology Overview
This study employs a novel hybrid Logarithmic Percentage Change-driven Objective Weighting (LOPCOW) and Multi-Attributive Border Approximation Area Comparison (MABAC) framework. The LOPCOW method ensures objective criteria weighting based on distance measures, while MABAC provides a stable ranking of alternatives by assessing their proximity to border approximation areas. The q-rung picture fuzzy set (q-PFS) environment is utilized to quantify uncertainty and ambiguity in decision-making, offering a robust approach for evaluating vertical farming technologies.
Aquaponics
Ranked as the Ideal Vertical Farming Method
Key Findings on VFTs
The research concludes that aquaponics is the ideal vertical farming method, followed by aeroponics, fogponics, and hydroponics. Production yield and energy consumption are identified as the most significant criteria influencing optimal VFT selection. Aquaponics excels by offering high yields and additional profit through fish rearing. Aeroponics is a strong alternative when fish rearing is not feasible, known for minimal resource usage and waste. Hydroponics, despite being the oldest method, ranks last among the evaluated VFTs due to newer techniques offering better overall performance.
VFT Comparison Matrix
| Method | Key Advantages | Considerations |
|---|---|---|
| Aquaponics |
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| Aeroponics |
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| Fogponics |
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| Hydroponics |
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Case Study: Urban Farming Initiative
A major urban development project faced challenges with limited land for agriculture and diminishing youth interest in traditional farming. The proposed hybrid LOPCOW-MABAC framework was applied to select an optimal vertical farming solution for integrated residential and commercial zones. After evaluating various VFTs against economic, performance, and sustainability criteria, aquaponics was chosen for its superior production yield and dual revenue streams from both crops and fish. This led to increased food security, reduced carbon footprint, and engaged local communities in sustainable agricultural practices within the urban environment. The framework's objective assessment minimized bias and ensured a data-driven decision, resulting in a successful, high-yield urban farm that maximized profit and minimized resource usage.
Enterprise Application Insights
The robust decision framework developed in this study has broad applicability across various enterprise scenarios. For agricultural enterprises, it provides a clear, objective method for selecting the most profitable and sustainable farming technologies. In supply chain management, it can optimize vendor selection by evaluating suppliers against multiple criteria, including cost, reliability, and environmental impact. For waste management, the framework can aid in choosing the most efficient and sustainable waste treatment technologies. Furthermore, its ability to quantify uncertainty makes it suitable for strategic decision-making in environments with complex, ambiguous data, ensuring optimal resource allocation and risk mitigation.
Quantify Your Vertical Farming ROI
Use our calculator to estimate potential savings and reclaimed productivity for your specific enterprise context with optimized Vertical Farming Techniques.
Annual Cost Savings
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Total Hours Reclaimed Annually
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Your Enterprise AI Implementation Timeline
A structured approach to integrating advanced decision frameworks for vertical farming in your operations.
Phase 1: Strategic Assessment & Data Collection
Evaluate current farming practices, identify key objectives (yield, cost, sustainability), and gather relevant operational data. Define performance metrics and establish a baseline for comparison. This phase ensures a clear understanding of your specific needs and challenges.
Phase 2: Framework Customization & Modeling
Customize the LOPCOW-MABAC framework with q-PFS to align with your enterprise's unique criteria and constraints. Build decision models, incorporating expert insights and historical data, to simulate and analyze various VFT scenarios. This involves setting up linguistic scales and fuzzy parameters.
Phase 3: Technology Selection & Pilot Program
Apply the robust decision framework to objectively rank and select the optimal vertical farming technology (e.g., Aquaponics, Aeroponics) for your pilot program. Implement a small-scale pilot to test the chosen VFT, validate the framework's predictions, and fine-tune operational parameters.
Phase 4: Full-Scale Integration & Performance Monitoring
Scale up the selected VFT across your operations, leveraging insights from the pilot. Establish continuous monitoring systems to track key performance indicators (KPIs) like yield, energy consumption, and profitability. Regularly reassess and adapt the strategy based on real-time data and market changes.
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