A Tabu Search Approach for Capacitated Vehicle Routing with Pickup and Delivery in Motorcycle-Based Urban Logistics under Traffic and Weather Constraints

Abstract

Motorcycle-based couriers play an essential role in urban logistics due to their flexibility and efficiency in congested environments. However, limited vehicle capacity combined with simultaneous delivery and pickup activities makes route planning a complex optimization problem. This study addresses the Capacitated Vehicle Routing Problem with Pickup and Delivery (CVRPPD) for motorcycle couriers by incorporating traffic congestion and weather conditions into the travel cost model. A Tabu Search metaheuristic is proposed to optimize routing decisions while simultaneously determining the optimal number of vehicles under a dynamic load constraint. The objective function is formulated using a lexicographic approach, prioritizing the minimization of the number of vehicles followed by the minimization of total travel cost, which is influenced by distance, traffic level, and weather condition. Computational experiments were conducted on a dataset consisting of one depot and 50 customers, with a maximum vehicle capacity of 30 kg. The simulation results demonstrate that the proposed approach consistently identifies an optimal solution using five motorcycles, which corresponds to the theoretical lower bound derived from total pickup demand. All customers are served exactly once without violating capacity constraints, and the maximum vehicle load reaches the allowable limit of 30 kg. The total travel cost obtained is 1316.262, indicating efficient route construction under dynamic environmental conditions. These results confirm that Tabu Search is an effective and robust approach for solving CVRPPD in motorcycle-based urban logistics, particularly when realistic operational factors such as traffic congestion and weather variability are considered.