A Graph-Theoretic Optimization Model for Sustainable Urban Resource Distribution

Sustainable development requires efficient allocation of limited resources such as water, electricity, and food within rapidly growing urban environments. Mathematical modeling provides powerful tools to optimize these systems and reduce environmental impact. This paper proposes a graph-theoretic optimization model for sustainable urban resource distribution. The city infrastructure is modeled as a weighted graph where nodes represent consumption centers and edges represent transportation routes. A minimum-cost flow optimization framework is applied to minimize energy consumption and carbon emissions while satisfying demand constraints. The model integrates sustainability indicators into classical network optimization techniques. The proposed approach demonstrates how mathematical methods can contribute to more efficient and environmentally responsible urban planning.