dc.description.abstract | Several 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 |