Applying Ant Colony Optimization for Inventory Routing Problem to Improve the Performance in Distribution Chain: A Case Study of Vietnamese Garment Company

The garment industry holds a paramount position within the Vietnamese economy. However, global industries, due to the aftermath of economic recessions and the impacts of epidemics, have faced imperatives to curtail expenses and optimize operational processes to bolster competitiveness. In this context, a novel trend gaining prominence is the adoption of chain management through the Vendor-Managed Inventory (VMI) method. This advancement has been facilitated by digital technology platforms and the rapid progress of science and technology. Consequently, suppliers can now efficiently oversee the inventory levels of retail units. To address cost-related issues within the supply chain, such as transportation and inventory costs, significant attention has been directed towards the Inventory Routing Problem (IRP), both in terms of research and practical application. The IRP aims to minimize the overall costs within the supply chain by selecting optimal delivery routes for each customer point, while simultaneously satisfying criteria encompassing demand, inventory levels, delivery times, distance considerations, and the number of vehicles deployed. Presently, global research efforts have yielded an array of methodologies for tackling the IRP, encompassing exact algorithms and approximate algorithms. Nevertheless, approximate algorithms, including heuristics and metaheuristics, have gained increasing traction in solving the IRP. These approaches are particularly prized for their ability to address highly complex problems and generate near-optimal solutions within prescribed time constraints. Hence, this research undertakes a focused examination of the application of Ant Colony Optimization (ACO) to resolve the IRP within the context of the garment distribution chain in Vietnam.