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dc.contributor.advisorNguyen, Van Hop
dc.contributor.authorLe, Nguyen Hong Hanh
dc.date.accessioned2024-03-21T06:17:36Z
dc.date.available2024-03-21T06:17:36Z
dc.date.issued2022
dc.identifier.urihttp://keep.hcmiu.edu.vn:8080/handle/123456789/5142
dc.description.abstractSeveral container/truck loading planning projects and research have been developed in recent years due to their real-world necessity. This thesis manages to solve the truck loading problem of GS25 Inhouse, CJ Gemadept for multiple trucks systems with real-world assumptions such as trucks’ capacities, demands, etc. The Randomized Constructive Heuristics is used with the help of C++ to generate a reasonable plan for loading orders, satisfying the punctuation of the delivery, the maximum utilization of trucks, the minimal operation time, the successful fulfillment of stores’ needs as well as maximize the company’s profits. The first phase is to preprocess the original data by combining boxes satisfied particular conditions. The second phase is to group stores orders into smaller groups and arrange their sequence based on zone, priority value and size of the package. The final phase is to pack orders into each truck, which satisfies the load balance and follow the sequence found in the second phase. The result of this method is evaluated by the company’s result to prove its advantages in number of trucks used and utilization rate.en_US
dc.language.isoenen_US
dc.subjectTruck loading problemen_US
dc.titleTruck loading problem: A case study of GS25 inhouseen_US
dc.title.alternativeTruck loading problem: A case study of GS25 inhouseen_US
dc.typeThesisen_US


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