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Mathematical Model and Random Search Algorithm for the Optimal Planning Problem of Replacing Traditional Public Transport with Electric

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Abstract

We investigate the complex optimization problem that arises in the planning of the transition process from traditional public transport to electric transport. We define the assumptions, input and output parameters of the problem, as well as its mathematical model and a randomized algorithm for solving it. We also give an extensive bibliography of publications on the problem at hand.

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References

  1. http://zeeus.eu/uploads/publications/documents/zeeus-report2017-2018-final.pdf

  2. Nikolič, Z. and Živanovič, Z., The Contribution and Prospects of the Technical Development on Iimplementation of Electric and Hybrid Vehicles, in New Generation of Electric Vehicles, Stevic, Z., Ed., London: IntechOpen, 2012, chapter 2, pp. 27–66.

    Google Scholar 

  3. Li, J.-Q., Battery-Electric Transit Bus Developments and Operations: A Review, Int. J. Sustain. Transp. Technol., 2016, vol. 10, pp. 157–169.

    Article  Google Scholar 

  4. Ahmad, A., Khan, Z.A., Alam, M.S., and Khateeb, S., A Review of the Electric Vehicle Charging Techniques, Standards, Progression and Evolution of EV Technologies in Germany, Smart Sci., 2018, vol. 6, no. 1, pp. 36–53.

    Article  Google Scholar 

  5. Anderson, J.E., Lehne, M., and Hardinghaus, M., What Electric Vehicle Users Wwant: Real-World Preferences for Public Charging Infrastructure, Int. J. Sustain. Transp., 2018, vol. 12, no. 5, pp. 341–352.

    Article  Google Scholar 

  6. Todorovic, M. and Simic, M., Current State of the Transition to Electrical Vehicles, Smart Innovat. Syst. Technol., 2019, vol. 98, pp. 130–139.

    Article  Google Scholar 

  7. Barnitt, R., Case Study: Ebus Hybrid Electric Buses and Trolleys, National Renewable Energy Laboratory, Technical Report NREL/TP–540–38749, 2006.

    Book  Google Scholar 

  8. Wang, X. and González, J.A., Assessing Feasibility of Electric Buses in Small and Medium-Sized Communities, Int. J. Sustain. Transp., 2013, vol. 7, pp. 431–448.

    Article  Google Scholar 

  9. Erkkilä, K., Nylund, N.-O., Pellikka, A.-P., Kallio, M., Kallonen, S., Ojamo, S., Ruotsalainen, S., Pietikäinen, O., and Lajunen, A., eBUS—Electric Bus Test Platform in Finland, EVS27 Int. Battery, Hybrid and Fuel Cell Electric Vehicle Sympos., Barcelona, Spain, 2013.

    Google Scholar 

  10. Schmidt, J., Eisel, M., and Kolb, L.M., Assessing the Potential of Different Charging Strategies for Electric Vehicle Fleets in Closed Transport Systems, Energ. Policy, 2014, vol. 74, pp. 179–189.

    Article  Google Scholar 

  11. http://zeeus.eu/uploads/publications/documents/zeeus-local-demo-brochures-mergedcompressed.pdf.

  12. Foltyński, M., Electric Fleets in Urban Logistics, Procedia Social Behav. Sci., 2014, vol. 151, pp. 48–59.

    Article  Google Scholar 

  13. Rogge, M., Wollny, S., and Sauer, D.U., Fast Charging Battery Buses for the Electrification of Urban Public Transport—A Feasibility Study Focusing on Charging Infrastructure and Energy Storage Requirements, Energies, 2015, vol. 8, no. 5, pp. 4587–4606.

    Article  Google Scholar 

  14. Hanlin, J., Battery Electric Buses Smart Deployment, Zero Emission Bus Conf., London, 2016.

    Google Scholar 

  15. Olsson, O., Grauers, A., and Pettersson, S., Method to Analyze Cost Effectiveness of Different Electric Bus Systems, EVS29 Int. Battery, Hybrid and Fuel Cell Electric Vehicle Sympos., Montreal, 2016, pp. 1–12.

    Google Scholar 

  16. Eudy, L. and Jeffers, M., Foothill Transit Battery Electric Bus Demonstration Results: Second Report, National Renewable Energy Laboratory, Technical Report NREL/TP-5400-67698, 2017.

    Book  Google Scholar 

  17. Gao, Z., Lin, Z., LaClair, T.J., Liu, C., Li, J.-M., Birky, A.K., and Ward, J., Battery Capacity and Recharging Needs for Electric Buses in City Transit Service, Energy, 2017, vol. 122, pp. 588–600.

    Article  Google Scholar 

  18. Leou, R.-C. and Hung, J.-J., Optimal Charging Schedule Planning and Economic Analysis for Electric Bus Charging Stations, Energies, 2017, vol. 10, no. 4, 483.

    Article  Google Scholar 

  19. Christensen, L., Klauenberg, J., Kveiborg, O., and Rudolph, C., Suitability of Commercial Transport for a Shift to Electric Mobility with Denmark and Germany as Use Cases, Res. Transp. Econ., 2017, vol. 64, pp. 48–60.

    Article  Google Scholar 

  20. Khan, W., Ahmad, A., Ahmad, F., and Alam, M.S., A Comprehensive Review of Fast Charging Infrastructure for Electric Vehicles, Smart Sci., 2018, vol. 6, no. 3, pp. 256–270.

    Google Scholar 

  21. Xylia, M. and Silveira, S., The Role of Charging Technologies in Upscaling the Use of Electric Buses in Public Transport: Experiences from Demonstration Projects, Transport Res., Part A: Pol., 2018, vol. 118, pp. 399–415.

    Google Scholar 

  22. Gallet, M., Massier, T., and Hamacher, T., Estimation of the Energy Demand of Electric Buses Based on Real-World Data for Large-Scale Public Transport Networks, Appl. Energ., 2018, vol. 230, pp. 344–356.

    Article  Google Scholar 

  23. Morganti, E. and Browne, M., Technical and Operational Obstacles to the Adoption of Electric Vans in France and the UK: An Operator Perspective, Transport Policy, 2018, vol. 63, pp. 90–97.

    Article  Google Scholar 

  24. Feng, W. and Figliozzi, M., Conventional vs Electric Commercial Vehicle Fleets: A Case Study of Economic and Technological Factors Affecting the Competitiveness of Electric Commercial Vehicles in the USA, Procedia Social Behav. Sci., 2012, vol. 39, pp. 702–711.

    Article  Google Scholar 

  25. Feng, W. and Figliozzi, M., An Economic and Technological Analysis of the Key Factors Affecting the Competitiveness of Electric Commercial Vehicles: A Case Study from the USA Market, Transport Res., Part C: Emer., 2013, vol. 26, pp. 135–145.

    Article  Google Scholar 

  26. Hallmark, S.L., Wang, B., and Sperry, R., Comparison of On-Road Emissions for Hybrid and Regular Transit Buses, J. Air Waste Manage., 2013, vol. 63, no. 10, pp. 1212–1220.

    Article  Google Scholar 

  27. Lajunen, A., Energy Consumption and Cost-Benefit Analysis of Hybrid and Electric City Buses, Transport Res., Part C: Emer., 2014, vol. 38, pp. 1–15.

    Article  Google Scholar 

  28. Mohamed, M., Garnett, R., Ferguson, M.R., and Kanaroglou, P., Electric Buses: A Review of Alternative Powertrains, Renew. Sust. Energ. Rev., 2016, vol. 62, pp. 673–684.

    Article  Google Scholar 

  29. Schoch, J., Modeling of Battery Life Optimal Charging Strategies Based on Empirical Mobility Data, Inform. Technol., 2016, vol. 58, no. 1, pp. 22–28.

    Google Scholar 

  30. Teoh, T., Kunze, O., and Teo, C.-C., Methodology to Evaluate the Operational Suitability of Electromo-bility Systems for Urban Logistics Operations, Transportation Res. Procedia, 2016, vol. 12, pp. 288–300.

    Article  Google Scholar 

  31. Teoh, T., Kunze, O., and Teo, C.-C., Scenario-Based Electric Bus Operation: A Case Study of Putrajaya, Malaysia, Int. J. Transp. Sci. Technol., 2018, vol. 7, no. 1, pp. 10–25.

    Article  Google Scholar 

  32. Mohamed, M., Farag, H., El-Taweel, N., and Ferguson, M., Simulation of Electric Buses on a Full Transit Network: Operational Feasibility and Grid Impact Analysis, Electr. Pow. Syst. Res., 2017, vol. 142, pp. 163–175.

    Article  Google Scholar 

  33. Marmaras, C., Xydas, E., and Cipcigan, E., Simulation of Electric Vehicle Driver Behaviour in Road Transport and Electric Power Networks, Transport Res., Part C: Emer., 2017, vol. 80, pp. 239–256.

    Article  Google Scholar 

  34. Xylia, M., Leduc, S., Patrizio, P., Silveira, S., and Kraxner, F., Developing a Dynamic Optimization Model for Electric Bus Charging Infrastructure, Transport. Res. Procedia, 2017, vol. 27, pp. 776–783.

    Article  Google Scholar 

  35. Fiori, C., Ahn, K., and Rakha, H.A., Optimum Routing of Battery Electric Vehicles: Insights Using Empirical Data and Microsimulation, Transport Res., Part D: Tr. E, 2018, vol. 64, pp. 262–272.

    Article  Google Scholar 

  36. Alonso, M., Amaris, H., Germain, J.G., and Galan, J.M., Optimal Charging Scheduling of Electric Vehicles in Smart Grids by Heuristic Algorithm, Energies, 2014, vol. 7, pp. 2449–2475.

    Article  Google Scholar 

  37. Wen, M., Laporte, G., Madsen, O.B.G., Norrelund, A.V., and Olsen, A., Locating Replenishment Stations for Electric Vehicles: Application to Danish Traffic Data, J. Oper. Res. Soc., 2014, vol. 65, no. 10, pp. 1555–1561.

    Article  Google Scholar 

  38. Yu, Z., Chen, S., and Tong, L., An Intelligent Energy Management System for Large-Scale Charging of Electric Vehicles, CSEE J. Power Energy, 2016, vol. 2, no. 1, pp. 47–53.

    Article  Google Scholar 

  39. Juan, A.A., Mendez, C.A., Faulin, J., de Armas, J., and Grasman, S.E., Electric Vehicles in Logistics and Transportation: A Survey on Emerging Environmental, Strategic, and Operational Challenges, Energies, 2016, vol. 9, no. 2, 86.

    Article  Google Scholar 

  40. Hiermann, G., Puchinger, G., Ropke, S., and Hartl, R.F., The Electric Fleet Size and Mix Vehicle Routing Problem with Time Windows and Recharging Stations, Eur. J. Oper. Res., 2016, vol. 252, pp. 995–1018.

    Article  MathSciNet  MATH  Google Scholar 

  41. Quak, H., Nesterova, N., and van Rooijen, T., Possibilities and Barriers for Using Electric-Powered Vehicles in City Logistics Practice, Transport. Res. Procedia, 2016, vol. 12, pp. 157–169.

    Article  Google Scholar 

  42. Desaulniers, G., Errico, F., Irnich, S., and Schneider, M., Exact Algorithms for Electric Vehicle-Routing Problems with Time Windows, Oper. Res., 2016, vol. 64, no. 6, pp. 1388–1405.

    Article  MathSciNet  MATH  Google Scholar 

  43. Wielinski, G., Trépanier, M., and Morency, C., Electric and Hybrid Car Use in a Free-Floating Car Sharing System, Int. J. Sustain. Transp., 2017, vol. 11, no. 3, pp. 161–169.

    Article  Google Scholar 

  44. Kunith, A., Mendelevitch, R., and Goehlich, D., Electrification of a City Bus Network—An Optimization Model for Cost-Effective Placing of Charging Infrastructure and Battery Sizing of Fast-Charging Electric Bus Systems, Int. J. Sustain. Transp., 2017, vol. 11, no. 10, pp. 707–720.

    Article  Google Scholar 

  45. Bruglieri, M., Mancini, S., Pezzella, F., Pisacane, O., and Suraci, S., A Three-Phase Matheuristic for the Time-Effective Electric Vehicle Routing Problem with Partial Recharges, Electron. Notes Discrete Math., 2017, vol. 58, pp. 95–102.

    Article  MathSciNet  MATH  Google Scholar 

  46. Pelletier, S., Jabali, O., and Laporte, G., Battery Electric Vehicles for Freight Distribution: A Survey of Vehicle Technology, Market Penetration, Incentives and Practices, CIRRELT-2014-43, Montreal: CIRRELT, 2014.

    Google Scholar 

  47. Pelletier, S., Jabali, O., and Laporte, G., 50th Anniversary Invited Article. Goods Distribution with Electric Vehicles: Review and Research Perspectives, Transport Sci., 2016, vol. 50, no. 1, pp. 3–22.

    Article  Google Scholar 

  48. Pelletier, S., Jabali, O., and Laporte, G., Charge Scheduling for Electric Freight Vehicle, Transport Res., Part B: Meth., 2018, vol. 115, pp. 246–269.

    Article  Google Scholar 

  49. Pelletier, S., Jabali, O., Laporte, G., and Veneroni, M., Battery Degradation and Behaviour for Electric Vehicles: Review and Numerical Analyses of Several Models, Transport Res., Part B: Meth., 2017, vol. 103, pp. 158–187.

    Article  Google Scholar 

  50. Froger, A., Mendoza, J., Jabali, O., and Laporte, G., New Formulations for the Electric Vehicle Routing Problem with Nonlinear Charging Functions, CIRRELT-2017-30, Montreal: CIRRELT, 2017.

    Google Scholar 

  51. Froger, A., Mendoza, J., Jabali, O., and Laporte, G., A Matheuristic for the Eectric Vehicle Routing Problem with Capacitated Charging Stations, CIRRELT-2017-31, Montreal: CIRRELT, 2017.

    Google Scholar 

  52. Xylia, M., Leduc, S., Patrizio, P., Kraxner, F., and Silveira, S., Locating Charging Infrastructure for Electric Buses in Stockholm, Transport Res., Part C: Emer., 2017, vol. 78, pp. 183–200.

    Article  Google Scholar 

  53. Liu, Z., Song, Z., and He, Y., Planning of Fast-Charging Stations for a Battery Electric Bus System under Energy Consumption Uncertainty, Transport Res. Rec., 2018. https://doi.org/10.1177/0361198118772953

    Google Scholar 

  54. Hosseini, S. and Sarder, M.D., Development of a Bayesian Network Model for Optimal Site Selection of Electric Vehicle Charging Station, Int. J. Elec. Power, 2019, vol. 105, pp. 110–122.

    Article  Google Scholar 

  55. Wang, Y., Bi, J., Guan, W., and Zhao, X., Optimising Route Choices for the Travelling and Charging of Battery Electric Vehicles by Considering Multiple Objectives, Transport Res., Part D: Transport Environ., 2018, vol. 64, pp. 246–261.

    Article  Google Scholar 

  56. Wang, Y.-W., Lin, C.-C., and Lee, T.-J., Electric Vehicle Tour Planning, Transport Res., Part D: Transport Environ., 2018, vol. 63, pp. 121–136.

    Article  Google Scholar 

  57. Quantification of the Health Effects of Exposure to Air Pollution, World Health Organization, Report of a WHO Working Group, Netherlands: Bilthoven, 2000.

  58. Sydbom, A., Blomberg, A., Parnia, S., Stenfors, N., Sandström, T, and Dahlén, S.E., Health Effects of Diesel Exhaust Emissions, Eur. Respir. J., 2001, vol. 17, no. 4, pp. 733–746.

    Article  Google Scholar 

  59. HEI Panel on the Health Effects of Traffic-Related Air Pollution. Traffic-Related Air Pollution: A Critical Review of the Literature on Emissions, Exposure, and Health Effects, HEI Special Report 17, Boston: Health Effects Institute, 2010.

  60. HEI Diesel Epidemiology Panel. Executive Summary. Diesel Emissions and Lung Cancer: An Evaluation of Recent Epidemiological Evidence for Quantitative Risk Assessment, HEI Special Report 19, Boston: Health Effects Institute, 2015.

  61. Ali, R., Effect of Diesel Emissions on Human Health: A Review, Int. J. Appl. Engin. Res., 2011, vol. 6, no. 11, pp. 1333–1342.

    Google Scholar 

  62. Chan, S., Miranda-Moreno, L.F., and Patterson, Z., Analysis of GHG Emissions for City Passenger Trains: Is Electricity an Obvious Option for Montreal Commuter Trains?, J. Transport. Technol., 2013, vol. 3, no. 2A, pp. 17–29.

    Article  Google Scholar 

  63. IARC Working Group on the Evaluation of Carcinogenic Risk to Humans. Diesel and Gasoline Engine Exhausts and Some Nitroarenes, IARC Monographs on the Evaluation of Carcinogenic Risks to Humans, no. 105, Lyon: Int. Agency for Research on Cancer, 2014.

  64. Mohner, M., The Hidden Impact of a Healthy-Worker Effect on the Results of the Diesel Exhaust in Miners Study, Eur. J. Epidemiol., 2016, vol. 31, no. 8, pp. 803–804.

    Article  Google Scholar 

  65. McClellan, R.O., Critique of Health Effects Institute Special Report 19, “Diesel Emissions and Lung Cancer: An Evaluation of Recent Epidemiological Evidence for Quantitative Risk Assessment,” Report, Albuquerque, 2016.

    Google Scholar 

  66. Gaskins, A.J., Hart, J.E., Mínguez-Alarcón, L., Chavarro, J.E., Laden, F., Coull, B.A., Ford, J.B., Souter, I., and Hauser, R., Residential Proximity to Major Roadways and Traffic in Relation to Outcomes of in vitro Fertilization, Environ. Int., 2018, vol. 115, pp. 239–246.

    Article  Google Scholar 

  67. Jochem, P., Plötz, P., Ng, W.-S., and Rothengatter, W., The Contribution of Electric Vehicles to Environmental Challenges in Transport, Transport Res., Part D: Tr. E, 2018, vol. 64, pp. 1–4.

    Article  Google Scholar 

  68. Steuer, R., Multiple Criteria Optimization: Theory, Computation and Application, New York: Wiley, 1985.

    MATH  Google Scholar 

  69. Vincke, P., Multicriteria Decision Aid, New York: Wiley, 1992.

    MATH  Google Scholar 

  70. Roy, B., Multicriteria Methodology for Decision Aiding, Nonconvex Optim. Appl., vol. 12, Dordrecht: Kluwer, 1996.

  71. Collette, Y. and Siarry, P., Multiobjective Optimization: Principles and Case Studies, New York: Springer Science & Business Media, 2004.

    Book  MATH  Google Scholar 

  72. Ehrgott, M., Multicriteria Optimization, New York: Springer Verlag, 2005.

    MATH  Google Scholar 

  73. Clerc, M., Particle Swarm Optimization, New York: Wiley, 2010.

    MATH  Google Scholar 

  74. Kennedy, J. and Eberhart, R., Particle Swarm Optimization, Proc. IEEE Int. Conf. on Neural Networks, Perth, Australia, 1995, pp. 1942–1948.

    Chapter  Google Scholar 

  75. Pedersen, M.E.H. and Chipperfield, A.J., Simplifying Particle Swarm Optimization, Appl. Soft Comput., 2010, vol. 10, pp. 618–628.

    Article  Google Scholar 

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Acknowledgments

The authors are grateful to Y.M. Shafransky, Lead Researcher of the UIIP NAS Belarus, for discussing the problem setting and useful suggestions for its modeling. initiative.

Funding

The work was carried out as part of the PLATON project of the ERA-NET Cofund Electric Mobility Europe

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Authors and Affiliations

  1. United Institute of Informatics Problems, National Academy of Sciences of Belarus, Minsk, Belarus

    M. Y. Kovalyov, B. M. Rozin & N. N. Guschinsky

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  1. M. Y. Kovalyov
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  2. B. M. Rozin
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  3. N. N. Guschinsky
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Correspondence to M. Y. Kovalyov, B. M. Rozin or N. N. Guschinsky.

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This paper was recommended for publication by A. A. Lazarev, a member of the Editorial Board

Russian Text © The Author(s), 2020, published in Avtomatika i Telemekhanika, 2020, No. 5, pp. 41–59.

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Kovalyov, M.Y., Rozin, B.M. & Guschinsky, N.N. Mathematical Model and Random Search Algorithm for the Optimal Planning Problem of Replacing Traditional Public Transport with Electric. Autom Remote Control 81, 803–818 (2020). https://doi.org/10.1134/S0005117920050033

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