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Sergio A. Caballero. Zipperer, Damaris R Brown, Andrew N Massachusetts Institute of Technology. Supply Chain Management Program. Massachusetts Institute of Technology. Supply Chain Management Program 2017-12-20T18:14:52Z 2017-12-20T18:14:52Z 2017 2017 http://hdl.handle.net/1721.1/112854 1014125398 Thesis: M. Eng. in Supply Chain Management, Massachusetts Institute of Technology, Supply Chain Management Program, 2017. Cataloged from PDF version of thesis. Includes bibliographical references (pages 51-52). Supply chains are facing increasingly volatile environments. Traditional optimization solutions provide a baseline understanding for industry applications, but cost-efficient solutions require a more robust approach. In high-tech capital construction projects, the construction of facilities requires complex project schedules, forecast well in advance. These forecasts are used to hire contract workers of varying contract lengths. In this thesis, we develop a risk integration methodology for contract workforce hiring optimization, and explore the capability of generalizing this approach for other supply chain problems. We first create a risk-integrated, optimal solution for workforce hiring that strategically covers areas of high risk density in construction forecasts. We first develop a program to simulate schedule variations based on the associated risk parameters of the scheduled tasks. Using the risk statistics resulting from these simulated schedules, we build new schedule requirements using two different methods. The first method addresses the gap from a daily perspective (bottom-up), while the second method addresses it from an overall schedule perspective (top-down). These new requirements are each overlaid on the input schedule, re-optimized, and excess daily coverage is trimmed. Using both methods, we found that higher levels of risk coverage were achieved at lower costs than the traditional solutions. In the studied case for Intel, a 23% additional risk coverage was generated for equivalent cost. Ultimately, the results show that strategic risk integration can result in a lower final cost, and a generalized framework for risk integration can be applied across many supply chain problems. by Damaris R. Zipperer and Andrew N. Brown. M.Eng. in Supply Chain Management 72 pages eng Massachusetts Institute of Technology MIT theses may be protected by copyright. Please reuse MIT thesis content according to the MIT Libraries Permissions Policy, which is available through the URL provided. http://dspace.mit.edu/handle/1721.1/7582 Supply Chain Management Program. A generalized framework for optimization with risk Thesis application/pdf false Publication unknown unknown <Publication xmlns="https://www.openaire.eu/cerif-profile/1.1/" id="53231d34-1af9-4824-bbaa-5ea57501b87d"> <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>A generalized framework for optimization with risk</Title> <PublishedIn> <Publication> </Publication> </PublishedIn> <PublicationDate>2017</PublicationDate> <Authors> <Author> <DisplayName>Zipperer, Damaris R</DisplayName> <Affiliation> <OrgUnit> </OrgUnit> </Affiliation> </Author> <Author> <DisplayName>Brown, Andrew N</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>Supply Chain Management Program.</Keyword> <Abstract>Supply chains are facing increasingly volatile environments. Traditional optimization solutions provide a baseline understanding for industry applications, but cost-efficient solutions require a more robust approach. In high-tech capital construction projects, the construction of facilities requires complex project schedules, forecast well in advance. These forecasts are used to hire contract workers of varying contract lengths. In this thesis, we develop a risk integration methodology for contract workforce hiring optimization, and explore the capability of generalizing this approach for other supply chain problems. We first create a risk-integrated, optimal solution for workforce hiring that strategically covers areas of high risk density in construction forecasts. We first develop a program to simulate schedule variations based on the associated risk parameters of the scheduled tasks. Using the risk statistics resulting from these simulated schedules, we build new schedule requirements using two different methods. The first method addresses the gap from a daily perspective (bottom-up), while the second method addresses it from an overall schedule perspective (top-down). These new requirements are each overlaid on the input schedule, re-optimized, and excess daily coverage is trimmed. Using both methods, we found that higher levels of risk coverage were achieved at lower costs than the traditional solutions. In the studied case for Intel, a 23% additional risk coverage was generated for equivalent cost. Ultimately, the results show that strategic risk integration can result in a lower final cost, and a generalized framework for risk integration can be applied across many supply chain problems.</Abstract> <Access xmlns="http://purl.org/coar/access_right" > </Access> </Publication>