| dc.description.abstract | This study delves into the shortcomings of delivery service quality in recent times due to
the prominent factor of long transit times, which can be determined by unreasonable routing
processes and improper loading planning. Inefficient loading planning can lead to reloading
many times, thus wasting time. To address these issues, the study introduces the Vehicle
Routing Problem with Time Windows (VRPTW), focusing on optimizing routes while
adhering to strict delivery time requirements. Simultaneously, the Container Loading
Problem (CLP) is also exploited to make the problem more realistic. For businesses dealing
with a diverse range of large products, considering only the weight of the package proves
inadequate, risking inefficient space utilization or impractical solutions. The expected
outcome takes into account the customers visit order along with their loading solution with
the overall goal of minimizing travel distance. Due to the complexity of the problem, a
Mixed Integer Programming (MIP) approach is introduced to receive exact solutions. Then,
the hybrid algorithm is employed to assess the approach's ability to deliver equivalent
quality solutions. It consists of the Adaptive Large Neighborhood Search (ALNS)
metaheuristic for routing problem combined with the Deepest-Bottom-Left-Fill algorithm
for loading problem. Additionally, data samples collected from Vua Nem company are used
to provide a thorough evaluation of the algorithm's accuracy and consistency. The findings
indicate that hybrid algorithm produces more optimal solutions within significantly shorter
runtimes, especially for medium to large sized cases. | en_US |
