Improving the Efficiency of Hub Operations in a Less-than-Truckload Distribution Network

dc.contributor.authorBrown, Amy Michelleen
dc.contributor.committeechairEllis, Kimberly P.en
dc.contributor.committeememberMeller, Russell D.en
dc.contributor.committeememberTaylor, William J.en
dc.contributor.committeememberTaylor, Robert E.en
dc.contributor.departmentIndustrial and Systems Engineeringen
dc.date.accessioned2011-08-06T16:06:42Zen
dc.date.adate2003-09-01en
dc.date.available2011-08-06T16:06:42Zen
dc.date.issued2003-04-22en
dc.date.rdate2004-09-01en
dc.date.sdate2003-08-27en
dc.description.abstractThe less-than-truckload (LTL) industry is highly competitive, with recent average profit margins less than 3%. LTL shipments are routed through a network of service centers and hubs. The performance of the entire LTL distribution network is highly dependent on the speed and accuracy of the hub operations. The focus of this research effort is to improve hub operations in order to reduce costs and increase service performance levels. Specifically, new approaches are investigated for assigning trailers to dock doors and sequencing the unloading of shipments at hubs. This thesis reviews current industry practices and available research literature on hub operations. Solution approaches for the trailer-to-door assignment and freight sequencing problems are presented along with case study results. The main performance measures are bottleneck time, total labor time, and total travel distance. For the trailer-to-door assignment problem, also referred to as the hub layout problem, the three approaches investigated are the original approach, a semi-permanent approach, and a dynamic approach. For the freight sequencing problem, the five approaches evaluated are trailer-at-a-time, trailer-at-a-time with offloading, nearest neighbor within a group, nearest neighbor within a shared group, and nearest neighbor. The approaches are implemented in C++ and analyzed using data from a regional LTL carrier. The case study results indicate that the dynamic layout performs significantly better than the original and semi-permanent layout for total distance, total labor time, and bottleneck time. For total distance and total labor time, the dynamic layout with nearest neighbor sequencing is the preferred approach. For bottleneck time, the dynamic layout with trailer-at-a-time with offloading performs best, while the nearest neighbor sequencing approach performs almost as well. In general, the case study results indicate that a dynamic layout with either a trailer-at-a-time with offloading approach or a nearest neighbor approach offers the largest potential for improvement. The assumptions and results of the hub layout and freight sequencing approaches are further evaluated using a simulation model. The simulation model indicates that a dynamic layout with nearest neighbor sequencing offers the largest potential for improvement in a more realistic environment with probabilistic and dynamic events. The simulation results also indicate that the trailer-at-a-time with offloading approach may need to be modified to account for more realistic dock conditions. In summary, the approaches explored in this research offer significant opportunity to improve hub operations through reducing bottleneck time, total labor time, and total travel distance.en
dc.description.degreeMaster of Scienceen
dc.format.mediumETDen
dc.identifier.otheretd-08272003-130223en
dc.identifier.sourceurlhttp://scholar.lib.vt.edu/theses/available/etd-08272003-130223en
dc.identifier.urihttp://hdl.handle.net/10919/10131en
dc.publisherVirginia Techen
dc.relation.haspartThesisDocument.pdfen
dc.rightsIn Copyrighten
dc.rights.urihttp://rightsstatements.org/vocab/InC/1.0/en
dc.subjectCross Dockingen
dc.subjectFreight Distributionen
dc.subjectLess-than-Truckloaden
dc.subjectFreight Sequencingen
dc.subjectHub Layouten
dc.titleImproving the Efficiency of Hub Operations in a Less-than-Truckload Distribution Networken
dc.typeThesisen
thesis.degree.disciplineIndustrial and Systems Engineeringen
thesis.degree.grantorVirginia Polytechnic Institute and State Universityen
thesis.degree.levelmastersen
thesis.degree.nameMaster of Scienceen

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