Modular Share-a-Ride Problem: An Approach for Combined Passenger and Freight Transport

Abstract

This study introduces the modular share-a-ride problem (MSARP). In this problem, modular vehicles (MVs), individually dedicated to serving either passengers or parcels, can couple and decouple platoons at service nodes, thereby enabling combined passenger and freight transport. The objective is to determine the optimal routing, fleet allocation, and (de)coupling decisions to maximize total profit. The problem is firstly formulated as a mixed-integer linear programming (MILP) model. To solve medium- and large-scale instances efficiently, a Q-learning based adaptive large neighborhood search (QALNS) algorithm is then proposed, which incorporates Q-learning algorithm and novel operators. These optimization components jointly achieve high-quality platoons and solutions. Finally, through extensive numerical experiments, the efficiency of the proposed algorithm are validated. The economic advantage of combined passenger and freight transport is further demonstrated.