Decision Making Approaches to Improve Resilience in Food Supply Chains and Enhance Food Security Against Climate Change Risks

As far as food security is concerned, the world is challenged by growing resource scarcity, changing diets, environmental challenges, volatile prices, and supply chain disruptions. Various technological, political, economic, and social factors drive food system dynamics that fluctuate in terms of their impact on food security. Many studies have attempted to alleviate risks governing food systems as means to achieve food security by suggesting numerous modelling approaches and decision-making tools. The purpose of this paper is to design a composite indicator analysing the risk status of a set of trade partners supplying Qatar with a predetermined food basket. The latter involves perishable fruits and vegetables. To design risk indicators, a set of individual factors reflecting the impact of climate change, inclusive of seasonality and sudden risks, are considered. The evaluation of these risks is performed based on their impact on Qatar's demand satisfaction. Whereas the assessment is conducted using the Analytical Hierarchy Process (AHP). The second stage of this work formulates a multi-objective optimization model in MATLAB that determines the optimal network of suppliers to satisfy the local need of Qatar, considering their climate risk profiles and their production capacities. The purpose of the optimization framework is to identify the contribution percentage of each trading partner to the total demand for the predetermined food basket while minimizing economic costs and risk composite factors. Results of the study assert that diversifying trade partners is the most resilient option to satisfy local demands yet with a high economic cost.