The airport shuttle bus scheduling problem

Abstract

This paper introduces the airport shuttle bus scheduling problem (ASBSP) as a new practical scheduling variant. In this problem, a number of identical vehicles that have a specific number of available seats provides transfer service between the airport and the city centre. After making a transfer in one direction, the vehicle can either make a new transfer in the opposite direction depending on the availability and the schedule of the passengers or make an empty return to make a new transfer in the same direction. The vehicles can wait in either location until their next transfer. The passengers have certain time windows for the transfer in relation to their flight times and operational rules to satisfy customer satisfaction. This is a profit-seeking service where transfer requests can also be rejected. The ASBSP aims to prepare a daily schedule for the available vehicles and to assign passengers to these vehicles with the objective of maximising the total profit. This paper presents two alternative mixed integer programming formulations and proposes two valid inequalities to get better bounds. Furthermore, it develops a hybrid metaheuristic that integrates multi-start, simulated annealing and large neighbourhood search for its solution. Extensive computational experiments on real-life benchmark instances have been made to test the performances of the formulations and the hybrid metaheuristic. Furthermore, the impacts of several problem parameters including the number of vehicles, vehicle capacity, transfer fee, transportation time and allowable passenger waiting times on the problem complexity and results have been investigated.

Keywords:

• Airport shuttle bus service
• scheduling
• hybrid metaheuristic

Acknowledgments

The authors gratefully acknowledge funding provided by the Scientific Research Projects Coordination Unit of Social Sciences University of Ankara under grant SBF-2019-190.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Notes on contributors

Nihat Öner

Nihat Öner is a Ph.D. candidate in Industrial Engineering at TOBB University of Economics and Technology. Before starting his degree, he earned his B.Sc. and M.Sc. at the same university in Turkey. During his M.Sc., he worked as project assistant funded by the Scientific and Technological Research Council of Turkey grant. He received an outstanding success scholarship from the same university. He is interested in cooperative game theory, cooperative logistics, routing problems, network optimization and heuristic algorithms.

Hakan Gultekin

Hakan Gultekin received the B.Sc., M.Sc. and Ph.D. degrees in industrial engineering from Bilkent University, Ankara, Turkey, in 2000, 2002 and 2007, respectively. He has been an associate professor with the Department of Mechanical and Industrial Engineering, Sultan Qaboos University, Muscat, Oman, since September 2018. He has also been affiliated with the Department of Industrial Engineering, TOBB University of Economics and Technology, Ankara, since 2007. Before joining the TOBB University of Economics and Technology, he visited the University of Liège, Belgium, for his postdoctoral studies. His research interests include scheduling, optimisation modelling, and exact and heuristic algorithm development, especially for problems arising in communication and logistics systems, modern manufacturing systems, energy systems, and wireless sensor networks.

Çağrı Koç

Çağrı Koç is an Associate Professor in Department of Business Administration at Social Sciences University of Ankara (ASBU). Prior to joining the ASBU in 2017, he worked as a Postdoctoral Fellow at HEC Montreal and at CIRRELT. He received his Ph.D. degree (2015) in Operational Research/Management Science from the Southampton Business School of University of Southampton. He is the recipient of the Doctoral Award from the Operational Research Society (2015), the Scientific and Technological Research Council of Turkey (TÜBİTAK) CAREER Award (2019) and Postgraduate Publication Awards from the University of Southampton. His research mainly focuses on the application of mathematical and metaheuristic optimization techniques to transportation, logistics and supply chain management problems, more specifically to vehicle routing and scheduling problems.