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Stanley Gershwin and Stephen Graves. Guasch Rodriguez, David Leaders for Global Operations Program. Leaders for Global Operations Program at MIT Massachusetts Institute of Technology. Department of Mechanical Engineering Sloan School of Management 2013-09-24T19:36:00Z 2013-09-24T19:36:00Z 2013 2013 http://hdl.handle.net/1721.1/80998 857789292 Thesis (M.B.A.)--Massachusetts Institute of Technology, Sloan School of Management; and, (S.M.)--Massachusetts Institute of Technology, Dept. of Mechanical Engineering; in conjunction with the Leaders for Global Operations Program at MIT, 2013. Cataloged from PDF version of thesis. Includes bibliographical references (p. 56-57). Compared to legacy retailers, online retailers have the potential to better accommodate buyer needs by offering more service time and inventory options. One fundamental operational challenge faced by most online businesses is designing a cost effective distribution network. Based on a fixed number of locations with finite resources, companies strive for finding the cost minimizing formula for fulfilling each customer order while meeting rigorous time constraints. In practice this involves allocating specific geographies to each warehouse and defining the logistic routes serving each customer. In an attempt to address this question, a Mixed Integer Linear Programming model has been developed as a decisionmaking tool for determining the optimal carrier-destination combination at each facility. The resulting algorithm is capable of analyzing thousands of potential shipping lanes and selecting those that minimize overall shipping cost. Based on historical data from customer orders, the model consistently finds an optimal network configuration yielding operational savings on the order of 1.5%. Furthermore, the algorithm can be used to identify near-optimal solutions requiring minor tweaks on the current configuration that produce significant economic gains. This simulation tool can be used on a regular basis to adapt the outbound network to demand fluctuations. However, this phenomenon evinces the existence of a fine trade-off between economic gains and operational feasibility. For that reason, a heuristic for selecting the most robust solution is also proposed. by David Guasch Rodriguez. S.M. M.B.A. 57 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 Sloan School of Management. Mechanical Engineering. Leaders for Global Operations Program. Reducing total fulfillment costs through distribution network design optimization Thesis application/pdf false Publication unknown unknown <Publication xmlns="https://www.openaire.eu/cerif-profile/1.1/" id="8eb2d23b-b554-4d4e-ba60-eee870af68d8"> <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>Reducing total fulfillment costs through distribution network design optimization</Title> <PublishedIn> <Publication> </Publication> </PublishedIn> <PublicationDate>2013</PublicationDate> <Authors> <Author> <DisplayName>Guasch Rodriguez, David</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>Sloan School of Management.</Keyword> <Keyword>Mechanical Engineering.</Keyword> <Keyword>Leaders for Global Operations Program.</Keyword> <Abstract>Compared to legacy retailers, online retailers have the potential to better accommodate buyer needs by offering more service time and inventory options. One fundamental operational challenge faced by most online businesses is designing a cost effective distribution network. Based on a fixed number of locations with finite resources, companies strive for finding the cost minimizing formula for fulfilling each customer order while meeting rigorous time constraints. In practice this involves allocating specific geographies to each warehouse and defining the logistic routes serving each customer. In an attempt to address this question, a Mixed Integer Linear Programming model has been developed as a decisionmaking tool for determining the optimal carrier-destination combination at each facility. The resulting algorithm is capable of analyzing thousands of potential shipping lanes and selecting those that minimize overall shipping cost. Based on historical data from customer orders, the model consistently finds an optimal network configuration yielding operational savings on the order of 1.5%. Furthermore, the algorithm can be used to identify near-optimal solutions requiring minor tweaks on the current configuration that produce significant economic gains. This simulation tool can be used on a regular basis to adapt the outbound network to demand fluctuations. However, this phenomenon evinces the existence of a fine trade-off between economic gains and operational feasibility. For that reason, a heuristic for selecting the most robust solution is also proposed.</Abstract> <Access xmlns="http://purl.org/coar/access_right" > </Access> </Publication>