Sustainable Decision-Making for Efficient Resource Management: A Food Security Case Study

Food security is one of the most pressing current resource management problems. It has become a concern for many countries in the light of changing climatic conditions, unpredictable instabilities and increasing consumption of resources. The purpose of this thesis is to address food availability as part of the food security challenge, through suggesting a modular framework that tackles major complexities hindering efficient decision-making within the food sector. The methodology suggested is based on a bottom up approach comprised, aiming at a first stage, at enhancing local production. Three decision-making techniques are used as part of this research thesis. The first module is based on a combination of single-objective optimization models based on linear programming, stochastic programming, and game theory approach. The results obtained demonstrate that interesting interactions between systems, albeit competitive, can potentially result in the achievement of desired objectives under properly regulated markets, and is therefore envisaged as a promising contribution towards sustainable policy development and nexus governance. The second module suggests a methodology that utilises the nexus thinking to influence decision-making within the food sector considering the uncertainty in natural gas prices. It assesses technology alternatives for a domestic food production case in Qatar based on economic and environmental performance represented by global warming potential (GWP). Findings indicate that diversifying the energy and water mix through introducing more than 70% of renewable energy technologies reduces the environmental impact. The last section of the thesis integrates international trade into the analysis of the food sector through proposing a dynamic decision-making scheme that simulates strategies of the perishable food market in Qatar under different circumstances. The case is modelled using an agent-based model (ABM).