Parallel ant colony optimization for vehicle routing with parcel lockers

Abstract

The recent surge in Vietnam’s e-commerce has significantly strained urban infrastructure, leading to increased last-mile delivery times, higher transportation costs, and diminished customer satisfaction. In response, many countries are adopting sustainable solutions like parcel lockers, which facilitate contactless deliveries. However, integrating parcel lockers introduces a new variant to the classic routing problem: the Vehicle Routing Problem with Parcel Lockers (VRPPL), which demands effective management of multiple delivery options. To address this, this research proposes a novel 3D Enhanced Parallel Ant Colony Optimization (3D-PACO) model. Our core contribution is the introduction of a pioneering multidimensional pheromone matrix to extend the traditional Ant Colony Optimization (ACO) for the VRPPL’s multiple delivery options. Further enhancing this, we propose an adaptive mechanism for dynamic ant allocation per thread for economical resource utilization. Finally, we adopt a master–slave parallel schema to the VRPPL enabling deployment of a large total number of ants. The experimental results on various VRPPL benchmark datasets indicate statistically significant improvements in solution quality with tremendous savings in computational runtime of 46.4% to 83.5% across different dataset sizes, compared to the original work.