Optimization for recipe-based, diet-planning inventory management

Abstract

This thesis presents a new modeling framework and research methodology for the study of recipe-based, diet-planning inventory management. The thesis begins with an exploration on the classic optimization problem - the diet problem based upon mixed-integer linear programming. Then, considering the fact that real diet-planning is sophisticated as it would be planning recipes rather than possible raw materials for the meals. Hence, the thesis develops the modeling framework under the assumption that given the recipes and the different purchasing options for raw materials listed in the recipes, examine the nutrition facts and calculate the purchasing decisions and the yearly optimal minimum cost for food consumption. This thesis further discusses the scenarios for different groups of raw materials in terms of shelf-timing difference. To model this inventory management, the modeling implementation includes preprocess part and the optimization part: the formal part involves with conversion of customized selection to quantitative relation with stored recipes and measurement on nutrition factors; the latter part solves the cost optimization problem.