Multi-Objective Optimization for Food Availability under Economic and Environmental Risk Constraints

Bashar Hassna, Sarah Namany, Mohammad Alherbawi, Adel Elomri and Tareq Al-Ansari ()
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Bashar Hassna: College of Science and Engineering, Hamad Bin Khalifa University, Doha P.O. Box 34110, Qatar
Sarah Namany: College of Science and Engineering, Hamad Bin Khalifa University, Doha P.O. Box 34110, Qatar
Mohammad Alherbawi: College of Science and Engineering, Hamad Bin Khalifa University, Doha P.O. Box 34110, Qatar
Adel Elomri: College of Science and Engineering, Hamad Bin Khalifa University, Doha P.O. Box 34110, Qatar
Tareq Al-Ansari: College of Science and Engineering, Hamad Bin Khalifa University, Doha P.O. Box 34110, Qatar

Sustainability, 2024, vol. 16, issue 11, 1-18

Abstract: Food security remains a critical global challenge, increasingly threatened by the adverse effects of climate change on agricultural productivity and food supply chains. Ensuring the stability, availability, and accessibility of food resources necessitates innovative strategies to assess and mitigate climate-related risks. This study presents a comprehensive analysis of the impact of climate change on global food systems, focusing on the risk assessment and optimization of food supply chains from the perspective of importers. Deploying the Analytical Hierarchy Process (AHP), this study evaluates climate change risks associated with seven different suppliers for three key crops, considering a range of factors, including surface temperature, arable land, water stress, and adaptation policies. Utilizing these assessments, a multi-objective optimization model is developed and solved using MATLAB (R2018a)’s Genetic Algorithm, aiming to identify optimal suppliers to meet Qatar’s food demand, with consideration of the economic, environmental, and risk factors. The findings underscore the importance of a comprehensive approach in managing food supply chains and offer insights to enhance the resilience and sustainability of global food systems amid climate uncertainties. This study contributes to the literature by applying AHP and multi-objective optimization in climate risk management within food systems, providing valuable perspectives for policymakers and stakeholders in the agricultural sector. Furthermore, the multi-objective optimization model analyzed three crop networks, yielding total costs of USD 16 million, USD 6 million, and USD 10 million for tomatoes, onions, and cucumbers, respectively, with associated CO 2 eq emissions and risk percentages. The findings reveal concentrated global vegetable markets, with major importers accounting for over 60% of imports, though the leading importers differ across crops, highlighting regional demand and production disparities, potentially impacting food security and supply chain resilience.

Keywords: food security; climate change; risk assessment; supply chain optimization; analytical hierarchy process (AHP) (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2024
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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Persistent link: https://EconPapers.repec.org/RePEc:gam:jsusta:v:16:y:2024:i:11:p:4336-:d:1398787

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