Combined passenger and parcel transportation using a mixed fleet of electric and gasoline vehicles. (January 2022)

• Record Type: Journal Article
• Authors: Lu, Chung-Cheng; Diabat, Ali; Li, Yi-Ting; Yang, Yu-Min
• Is Part Of: Transportation research. Volume 157(2022)
• Publication Date: 2022-01
• Subjects: Combined passenger and parcel transportation -- Ride-sharing -- Electric taxis -- Time-expanded network -- Mixed integer linear program; Logistics -- Periodicals; Transportation -- Periodicals; 388.011
• DOI: 10.1016/j.tre.2021.102546
• Languages: English
• ISSNs: 1366-5545

Abstract

Highlights: Solve the combined passenger and parcel transportation problem with a mixed fleet. Formulate the problem as a MILP model based on a multi-layer time-expanded network. Develop a network decomposition-based math-heuristic to efficiently solve the problem. Evaluate the model and the algorithm using real-world instances. Abstract: This study deals with a variant of the vehicle routing problem that aims to design the optimal routes for a mixed fleet of taxis that simultaneously services a given set of passenger and parcel requests. The fleet is composed of electric vehicles and gasoline vehicles. The problem is called combined passenger and parcel transportation problem with a mixed fleet (CPPT-MF). We construct a time-expanded network which is used to model the movements of passengers, parcels and vehicles in space and time. A mixed-integer linear programming model of the problem is developed on the basis of the time-expanded network. A network partitioning-based math-heuristic is proposed to efficiently solve large-scale instances of the problem. The model and the heuristic are evaluated using a set of real-world instances from a taxi company and a set of randomly generated instances. The computational results show that the proposed approach is effective and efficient for solving the CPPT-MF and could facilitate taxi companies with heterogeneous fleets for deciding the routes to simultaneously service passenger and parcel requests.