Published Paper Details:

Linear Programming was conceived in the period of the second world war to address defense needs. Dantzig, who developed LP modelling and simplex algorithms, tried to use LP for his personal diet plan (meeting his nutritional needs at minimum cost). He could not sustain the approach because of various factors. In the later history of LP modelling, diet problems have been addressed in various settings like hospitals, industries and with additional objectives like environmental impacts, cultural acceptance. One of UN Sustainability goals is meeting nutrition needs of children. In India programs like Akshaya Patra provide midday meals for school going children. Everyday millions of school kids are fed by such programs. Can we do what Dantzig did for himself (diet planning) for every school going kid? Such goals are now attainable and sustainable with modern developments. Quantum Computing and Artificial Intelligence will help us to realize this. Quantum computers using features of the quantum world (superposition and entanglement) allow us to solve problems which are not practically tractable for classical computers and provide exponential speedup in time. Quantum algorithms (like Quantum Approximation Quantum Algorithm) have been conceived for linear programming and tested. Artificial Intelligence can now provide user-friendly support for data extraction, model formulation, solution links and interpretation of results for action for various kinds of user settings. The paper develops a road map for Quantum AI Linear Programming decision support for personalized diet plans for members of massive organizations like national midday meals for school kids.