Optimization for recipe-based, diet-planning inventory management

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.

Department dc:contributor.department

Massachusetts Institute of Technology. Computation for Design and Optimization Program.

Grantor dc:publisher

Massachusetts Institute of Technology

Year dc:date.issued

2010

Author dc:creator

• Kang, Sheng

Advisor dc:contributor.advisor

• Richard Larson.

• Computation for Design and Optimization Program.

Statement dc:rights

• M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission.

Licence dc:rights.uri

• http://dspace.mit.edu/handle/1721.1/7582

Language dc:language.iso

eng

Handle dc:identifier.uri

http://hdl.handle.net/1721.1/61895

OAI identifier oai:identifier

oai:dspace.mit.edu:1721.1/61895