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Optimizing the Scheduling of Electrified Public Transport System in Malta

Author

Listed:
  • 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
    The Foundation for Innovation and Research—Malta, 65 Design Centre Level 2, Tower Road, BKR 4012 Birkirkara, Malta)

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.

Suggested Citation

  • Satish Sharma & Somesh Bhattacharya & Deep Kiran & Bin Hu & Matthias Prandtstetter & Brian Azzopardi, 2023. "Optimizing the Scheduling of Electrified Public Transport System in Malta," Energies, MDPI, vol. 16(13), pages 1-16, June.
    • Handle: RePEc:gam:jeners:v:16:y:2023:i:13:p:5073-:d:1183971
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    References listed on IDEAS

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    1. Richard Freling & Albert P. M. Wagelmans & José M. Pinto Paixão, 2001. "Models and Algorithms for Single-Depot Vehicle Scheduling," Transportation Science, INFORMS, vol. 35(2), pages 165-180, May.
    2. Borna Dasović & Uroš Klanšek, 2022. "A Review of Energy-Efficient and Sustainable Construction Scheduling Supported with Optimization Tools," Energies, MDPI, vol. 15(7), pages 1-17, March.
    3. Jing Teng & Shuang Jin & Xiongfei Lai & Sijin Chen, 2015. "Vehicle-Scheduling Model for Operation Based on Single-Depot," Mathematical Problems in Engineering, Hindawi, vol. 2015, pages 1-10, September.
    4. Aleksander Jagiełło & Marcin Wołek & Wojciech Bizon, 2023. "Comparison of Tender Criteria for Electric and Diesel Buses in Poland—Has the Ongoing Revolution in Urban Transport Been Overlooked?," Energies, MDPI, vol. 16(11), pages 1-17, May.
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