Optimizing the Scheduling of Electrified Public Transport System in Malta

被引:1
作者
Sharma, Satish [1 ]
Bhattacharya, Somesh [2 ]
Kiran, Deep [3 ]
Hu, Bin [4 ]
Prandtstetter, Matthias [4 ]
Azzopardi, Brian [5 ,6 ]
机构
[1] Malaviya Natl Inst Technol Jaipur, Dept Elect Engn, Jaipur 302017, India
[2] Univ Malta, Fac Engn, Dept Elect Engn, MSD-2080 Msida, Malta
[3] Indian Inst Technol Roorkee, Dept Elect Engn, Roorkee 247667, India
[4] Austrian Inst Technol, A-1210 Vienna, Austria
[5] Malta Coll Arts Sci & Technol MCAST, Inst Engn & Transport, MCAST Energy Res Grp, Main Campus,Corradino Hill, Paola 9032, Malta
[6] Fdn Innovat & Res Malta, 65 Design Ctr Level 2,Tower Rd, Birkirkara 4012, Malta
基金
欧盟地平线“2020”;
关键词
electric buses; scheduling problem; public transportation; multi-agent framework; sustainable transport; BUS;
D O I
10.3390/en16135073
中图分类号
TE [石油、天然气工业]; TK [能源与动力工程];
学科分类号
0807 ; 0820 ;
摘要
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.
引用
收藏
页数:16
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