Abstract
This paper presents a multi-objective optimization approach for the security assessment of the water–energy–food nexus considering the involved uncertainty. The proposed optimization approach consists of a hybrid strategy that combines deterministic and metaheuristic optimization approaches for solving this complex problem. The deterministic optimization part of the mathematical model is developed in the platform general algebraic modeling system (GAMS). The metaheuristic part is approached using the improved multi-objective optimization differential evolution algorithm programmed in visual basic for applications. The communication between the different software is implemented using GAMS data exchange files and linking routines. The uncertainty associated with the problem is considered using a code that generates random values of uncertain parameters of the mathematical model. The optimization approach is applied to assess the water–energy–food nexus in an arid region. Three objective functions (one economic and two environmental) were incorporated in the proposed formulation. A case study from a region of Mexico is addressed to show the applicability of the proposed approach. The results of the optimization process offer alternatives that conciliate economic and environmental interests considering uncertainty in weather conditions such as rainfall and solar radiation. The obtained results show a set of solution proposals in which different increases are offered in the satisfaction of the demand for energy and water in different sectors and at the same time, the smallest possible increase in the economic and environmental objective functions. In addition, the proposed methodology is replicable to different case studies where approaching the optimal solution becomes a complicated task.
Graphical abstract
Article Highlights
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Resources management of the water–energy–food nexus in an arid region.
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A hybrid metaheuristic–deterministic optimization method to solve complex problems.
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Multi-objective optimization to satisfy an increase in demand from different sectors.
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Minimize total costs, freshwater consumption, and greenhouse gas emissions.
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Consideration of uncertainty in weather conditions as rainfall and solar radiation.
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Abbreviations
- AMM:
-
Monterrey Metropolitan Area
- CF:
-
Crossover fraction
- E1:
-
Energy availability
- E2:
-
Energy accessibility
- E3:
-
Energy sustainability
- EOA:
-
Evolutionary optimization algorithm
- F:
-
Mutation fractions
- F1:
-
Food availability
- F2:
-
Food accessibility
- F3:
-
Food sustainability
- GAMS:
-
General algebraic modeling system
- GDP:
-
Gross domestic product
- GDX:
-
GAMS data eXchange
- HM3:
-
Hectometer cubic meters
- I-MODE:
-
Improved multi-objective differential evolution
- MILP:
-
Mixed-integer linear programming
- MINLP:
-
Mixed-integer non-lineal programming
- MNG:
-
Maximum numbers of generations
- MPM:
-
Mathematical programming model
- MS:
-
Microsoft
- MTon:
-
Millions of tons
- MUSD:
-
Millions of US Dollars
- PS:
-
Population size
- RLR:
-
Randomness and linking routines
- TAC:
-
Total annual cost
- TLS:
-
Taboo list size
- TOTFRESHW:
-
Total fresh water
- TOTGHGE:
-
Total green house gas emissions
- TR:
-
Taboo radius
- VBA:
-
Visual basic for applications
- W1:
-
Water availability
- W2:
-
Water accessibility
- W3:
-
Water sustainability
- WEF:
-
Water–energy–food
- WEFO:
-
Water–energy–food security nexus optimization model
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Acknowledgements
We are grateful to Mexico’s National Council for Science and Technology (Conacyt-FORDECYT/12SE/2018/11/29-05) for financial support. In addition, we acknowledge the financial support from CIC-UMSNH.
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Hernández-Pérez, L.G., Sánchez-Zarco, X.G. & Ponce-Ortega, J.M. Multi-objective Optimization Method Based on Deterministic and Metaheuristic Approaches in Water–Energy–Food Nexus Under Uncertainty. Int J Environ Res 16, 33 (2022). https://doi.org/10.1007/s41742-022-00411-y
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DOI: https://doi.org/10.1007/s41742-022-00411-y