Enhancing Food Resource Allocation in India: A Fuzzy Logic Approach Integrated with Julia and Python

Abstract

Exploring the intricate network of food resource distribution, especially in the Indian context, this research delves into the multifaceted challenges stemming from poverty and food insecurity. It offers a comprehensive analysis that includes historical perspectives, socio-economic conditions, government policies, and their impact on vulnerable communities. Using innovative methods such as fuzzy logic-based models, Lagrangian optimization, and the Graded Mean Integration (GMI) representation technique, the study provides a systematic approach to allocate resources effectively in food distribution inventory management. By employing the Julia programming language to define and illustrate data for three distinct regions, the research sheds light on critical factors like food poverty levels, budget constraints, demand, supply, inventory, and resource allocation. Additionally, the use of Python libraries for visual representation enhances our understanding of these crucial parameters. Ultimately, this research contributes to the ongoing effort to establish a more equitable and sustainable food distribution system, ensuring access to nutritious food for all individuals, thereby fostering both individual well-being and national prosperity.