Optimizing the Scheduling of Electrified Public Transport System in Malta

Satish Sharma, Somesh Bhattacharya (), Deep Kiran, Bin Hu, Matthias Prandtstetter and Brian Azzopardi
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Satish Sharma: Department of Electrical Engineering, Malaviya National Institute of Technology Jaipur, Jaipur 302017, India
Somesh Bhattacharya: Department of Electrical Engineering, Faculty of Engineering, University of Malta, MSD 2080 Msida, Malta
Deep Kiran: Department of Electrical Engineering, Indian Institute of Technology Roorkee, Roorkee 247667, India
Bin Hu: Austrian Institute of Technology, 1210 Vienna, Austria
Matthias Prandtstetter: Austrian Institute of Technology, 1210 Vienna, Austria
Brian Azzopardi: MCAST Energy Research Group, Institute of Engineering and Transport, Malta College of Arts, Science and Technology (MCAST), Main Campus, Corradino Hill, PLA 9032 Paola, Malta

Energies, 2023, vol. 16, issue 13, 1-16

Abstract: In this paper, we describe a comparative analysis of a bus route scheduling problem as part of timetable trips. We consider the current uptake of electric buses as a viable public transportation option that will eventually phase out the diesel-engine-based buses. We note that, with the increasing number of electric buses, the complexity related to the scheduling also increases, especially stemming from the charging requirement and the dedicated infrastructure behind it. The aim of our comparative study is to highlight the brevity with which a multi-agent-system-based scheduling method can be helpful as compared to the classical mixed-integer linear-programming-based approach. The multi-agent approach we design is centralized with asymmetric communication between the master agent, the bus agent, and the depot agent, which makes it possible to solve the multi-depot scheduling problem in almost real time as opposed to the classical optimizer, which sees a multi-depot problem as a combinatorial heuristic NP-hard problem, which, for large system cases, can be computationally inefficient to solve. We test the efficacy of the multi-agent algorithm and also compare the same with the MILP objective designed in harmony with the multi-agent system. We test the comparisons first on a small network and then extend the scheduling application to real data extracted from the public transport of the Maltese Islands.

Keywords: electric buses; scheduling problem; public transportation; multi-agent framework; sustainable transport (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2023
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