| dc.description.abstract | This thesis addresses the Multi-Allocation Hub Location Routing Problem
(MAHLRP) in the context of warehouse site selection and network design, focusing on Qui
Phuc Company as a case study. The study aims to enhance operational efficiency and cost effectiveness by integrating advanced heuristic algorithms, specifically the Adaptive Large
Neighborhood Search (ALNDS), into the MAHLRP model. The research is structured
around three main objectives: firstly, developing a systematic approach to identify optimal
warehouse locations based on demand patterns, transportation costs, and proximity to
allocation hubs; secondly, redesigning Qui Phuc Company’s logistics network to optimize
supplier allocation to main hub warehouses; and finally, reducing allocation routing and
last-mile delivery costs post-warehouse selection. Key findings demonstrate that ALNDS
outperforms traditional optimizers like CPLEX in solving MAHLRP, yielding significant
cost reductions and operational improvements for Qui Phuc Company. Specifically, the
algorithm’s adaptability and efficiency in handling large datasets and complex network
structures enable better decision-making in warehouse site selection and network design.
The study identifies Hub 5 in Da Nang as strategically advantageous, underscoring the
algorithm’s role in enhancing distribution efficiency and operational performance. These
results highlight the broader applicability of ALNDS in logistics and supply chain
optimization, offering businesses substantial improvements in operational efficiency, cost
savings, and market competitiveness. | en_US |
