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dc.contributor.advisorNdiaye, Malick
dc.contributor.advisorOsman, Mojahid Faroug Saeed
dc.contributor.authorQazi, Osama Saqib
dc.date.accessioned2019-06-09T07:36:32Z
dc.date.available2019-06-09T07:36:32Z
dc.date.issued2019-02
dc.identifier.other35.232-2019.23
dc.identifier.urihttp://hdl.handle.net/11073/16457
dc.descriptionA Master of Science thesis in Engineering Systems Management by Osama Saqib Qazi entitled, “Cargo Delivery Box System for the modelling of Last mile of B2C Logistics”, submitted in February 2019. Thesis advisor is Dr. Malick Ndiaye and thesis co-advisor is Dr. Mojahid Faroug Saeed Osman. Soft and hard copy available.en_US
dc.description.abstractThe current business trends suggest that the e-commerce business in the UAE is increasing rapidly, which means that the supply chain facilities must be improved to sustain efficiency and profitability. The last mile is highlighted to be the most expensive part of the supply chain. Therefore, optimizing the last mile can increase cost savings for the logistics companies and may even translate into reduced charges for the end consumer. The traditional approach of house to house delivery not only poses high costs but it also contributes to road congestions, delays in deliveries, fragmentation of deliveries and higher carbon emissions. The research showed a real gap in providing a solution that considers all aspects of delivery; the parcel routing, delivery mechanism but also the reception method for the convenience of the customer and the company alike. In this research, we propose a new solution, which calls for consolidating the deliveries from e-retailers at the urban consolidation centers. The urban consolidation center then groups the shipments according to their destinations, loads them on to the cargo delivery boxes. The cargo delivery boxes are then shipped to the corresponding locations using commercially economical vehicles. These potential delivery locations can be either restaurants, grocery stores or retail shops that are spread across the city and are easily in reach to the customers of that area. The customers would be able to collect their deliveries at their conveniences, and the delivery box is collected by the delivery vehicle at night. We formulated a two-stage approach solution and a consolidated model. We validated the models on many scenarios before finally testing the final model (Two-stage Solution) on a data set of five hundred customers, spread across two hundred and fifty-kilometer squares. Finally, the sensitivity analysis on the model showed that the customer footprint across a given area and the size range options of the cargo delivery boxes were the most sensitive parameters to the total last-mile cost.en_US
dc.description.sponsorshipCollege of Engineeringen_US
dc.description.sponsorshipDepartment of Industrial Engineeringen_US
dc.language.isoen_USen_US
dc.relation.ispartofseriesAmerican University of Sharjah Student Worken_US
dc.relation.ispartofseriesMaster of Science in Engineering Systems Management (MSESM)en_US
dc.subjectLast-mileen_US
dc.subjecte-commerceen_US
dc.subjectLogistics collaborationen_US
dc.subjectCargo delivery box modelen_US
dc.subjectCluster deliveryen_US
dc.subjectMissed deliveryen_US
dc.titleCargo Delivery Box System for modeling the Last mile of Business to Consumer Logisticsen_US
dc.typeThesisen_US


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