2026-09-20T16:34:36Zhttps://dspace.mit.edu/server/oai/request

oai:dspace.mit.edu:1721.1/618952022-01-13T07:54:53Zcom_1721.1_7582com_1721.1_7581col_1721.1_131023

Richard Larson. Kang, Sheng Massachusetts Institute of Technology. Computation for Design and Optimization Program. Massachusetts Institute of Technology. Computation for Design and Optimization Program 2011-03-24T20:23:02Z 2011-03-24T20:23:02Z 2010 2010 http://hdl.handle.net/1721.1/61895 706807732 Thesis (S.M.)--Massachusetts Institute of Technology, Computation for Design and Optimization Program, 2010. Cataloged from PDF version of thesis. Includes bibliographical references (p. 40-41). 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. by Sheng Kang. S.M. 41 p. eng Massachusetts Institute of Technology 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. http://dspace.mit.edu/handle/1721.1/7582 Computation for Design and Optimization Program. Optimization for recipe-based, diet-planning inventory management Thesis application/pdf false Publication unknown unknown <Publication xmlns="https://www.openaire.eu/cerif-profile/1.1/" id="b795cb2e-b417-4705-abe0-abb210eddd0b"> <Type xmlns="https://www.openaire.eu/cerif-profile/vocab/COAR_Publication_Types">http://purl.org/coar/resource_type/c_1843</Type> <Language>eng</Language> <Title>Optimization for recipe-based, diet-planning inventory management</Title> <PublishedIn> <Publication> </Publication> </PublishedIn> <PublicationDate>2010</PublicationDate> <Authors> <Author> <DisplayName>Kang, Sheng</DisplayName> <Affiliation> <OrgUnit> </OrgUnit> </Affiliation> </Author> </Authors> <Editors> </Editors> <Publishers> <Publisher> <DisplayName>Massachusetts Institute of Technology</DisplayName> <OrgUnit /> </Publisher> </Publishers> <License>http://dspace.mit.edu/handle/1721.1/7582</License> <Keyword>Computation for Design and Optimization Program.</Keyword> <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.</Abstract> <Access xmlns="http://purl.org/coar/access_right" > </Access> </Publication>