A coordinated optimization of rewarded users and employees in relocating station-based shared electric vehicles

• Autorzy: Yu Lan , Liu Jiaming , Sun Zhuo

Identyfikatory

DOI

10.34768/amcs-2022-0037

• Języki publikacji: EN

Abstrakty

EN

To solve the mismatch between the supply and demand of shared electric vehicles (SEVs) caused by the uneven distribution of SEVs in space and time, an SEV relocating optimization model is designed based on a reward mechanism. The aim of the model is to achieve a cost-minimized rebalancing of the SEV system. Users are guided to attend the relocating SEVs by a reward mechanism, and employees can continuously relocate multiple SEVs before returning to the supply site. The optimization problem is solved by a heuristic column generation algorithm, in which the driving routes of employees are added into a pool by column generation iteratively. In the pricing subproblem of column generation, the Shuffled Complex Evolution–University of Arizona (SCE–UA) is designed to generate a driving route. The proposed model is verified with the actual data of the Dalian city. The results show that our model can reduce the total cost of relocating and improve the service efficiency.

Słowa kluczowe

EN

shared electric vehicle; user reward mechanism; collaborative relocating; SCE–UA

PL

wspólny pojazd elektryczny; mechanizm nagradzania użytkowników; SCE–UA

• Wydawca: Oficyna Wydawnicza Uniwersytetu Zielonogórskiego
• Czasopismo: International Journal of Applied Mathematics and Computer Science
• Rocznik: 2022
• Tom: Vol. 32, no. 4
• Strony: 523--535
• Opis fizyczny: Bibliogr. 27 poz., rys., tab.

Twórcy

autor

Yu Lan

• School of Maritime Economics and Management, Dalian Maritime University, Dalian, 116026, PR China

autor

Liu Jiaming

• School of Transportation Science and Engineering, Beihang University, Beijing, 100191, PR China

autor

Sun Zhuo

• School of Maritime Economics and Management, Dalian Maritime University, Dalian, 116026, PR China

Bibliografia

• [1] Almeida, C.G.H.D. and Pais, A.A. (2012). Optimization approach to depot location and trip selection in one-way carsharing systems, Transportation Research E: Logistics and Transportation Review 48(1): 233–247.
• [2] Boyaci, B., Zografos, K.G. and Geroliminis, N. (2015). An optimization framework for the development of efficient one-way car-sharing systems, European Journal of Operational Research 240(3): 718–733.
• [3] Brandstatter, G., Kahr, M. and Leitner, M. (2017). Determining optimal locations for charging stations of electric car-sharing systems under stochastic demand, Transportation Research B: Methodological 104: 17–35.
• [4] Bruglieri, M., Colorni, A. and Lu, A. (2014). The vehicle relocation problem for the one-way electric vehicle sharing: An application to the Milan case, Procedia—Social and Behavioral Sciences 111: 18–27.
• [5] Bruglieri, M., Pezzella, F. and Pisacane, O. (2017). Heuristic algorithms for the operator-based relocation problem in one-way electric carsharing systems, Discrete Optimization 23: 56–80.
• [6] Cao, S., Shao, H. and Shao, F. (2022). Sensor location for travel time estimation based on the user equilibrium principle: Application of linear equations, International Journal of Applied Mathematics and Computer Science 32(1): 23–33, DOI: 10.34768/amcs-2022-0003.
• [7] Ciari, F., Schuessler, N. and Axhausen, K.W. (2013). Estimation of carsharing demand using an activity-based microsimulation approach: Model discussion and some results, International Journal of Sustainable Transportation 7(1): 70–84.
• [8] Deng, Y. and Cardin, M.-A. (2018). Integrating operational decisions into the planning of one-way vehicle-sharing systems under uncertainty, Transportation Research C: Emerging Technologies 86: 407–424.
• [9] Desrosiers, J. and Lübbecke, M.E. (2005). A primer in column generation, in G. Desaulniers et al. (Eds), Column Generation, Springer, Boston, pp. 1–32.
• [10] Desaulniers, G., Lessard, F. and Hadjar, A. (2008). Tabu search, partial elementarity, and generalized k-path inequalities for the vehicle routing problem with time windows, Transportation Science 42(3): 387–404.
• [11] Di Febbraro, A., Sacco, N. and Saeednia, M. (2019). One-way car-sharing profit maximization by means of user-based vehicle relocation, IEEE Transactions on Intelligent Transportation Systems 20(2): 628–641.
• [12] Duan, Q. (1991). A Global Optimization Strategy for Efficient and Effective Calibration of Hydrologic Models, PhD dissertation, 9208054, University of Arizona, Tucson.
• [13] Duan, Q., Gupta, V. and Sorooshian, S. (1993). Shuffled complex evolution approach for effective and efficient global minimization, Journal of Optimization Theory and Applications 76(3): 501–521.
• [14] Duan, Q., Sorooshian, S. and Gupta, V.K. (1994). Optimal use of the SCE–UA global optimization method for calibrating watershed models, Journal of Hydrology 158(3–4): 265–284.
• [15] Fassi, A.E., Awasthi, A. and Viviani, M. (2012). Evaluation of carsharing network’s growth strategies through discrete event simulation, Expert Systems with Applications 39(8): 6692–6705.
• [16] Feillet, D., Gendreau, M. and Rousseau, L.-M. (2007). New refinements for the solution of vehicle routing problems with branch and price, INFOR 45(4): 239–256.
• [17] Freedman, V.L., Lopes, V.L. and Hernandez, M. (1998). Parameter identifiability for catchment-scale erosion modelling: A comparison of optimization algorithms, Journal of Hydrology 207(1-2): 83–97.
• [18] Jorge, D. and Correia, G. (2013). Carsharing systems demand estimation and defined operations: A literature review, European Journal of Transport and Infrastructure Research 13(3): 201–220.
• [19] Kaspi, M., Raviv, T. and Tzur, M. (2014). Parking reservation policies in one-way vehicle sharing systems, Transportation Research B: Methodological 62: 35–50.
• [20] Thyer, M., Kuczera, G. and Bates, B.C. (1999). Probabilistic optimization for conceptual rainfall-runoff models: A comparison of the shuffled complex evolution and simulated annealing algorithms, Water Resources Research 35(3): 767–773.
• [21] Tian, Z., Feng, T., Timmermans, H.J. and Yao, B. (2021). Using autonomous vehicles or shared cars? Results of a stated choice experiment, Transportation Research C: Emerging Technologies 128: 103117.
• [22] Van Griensven, A. and Bauwens, W. (2003). Multiobjective autocalibration for semidistributed water quality models, Water Resources Research 39(12): SWC91–SWC99.
• [23] Wang, L., Liu, Q. and Ma, W. (2019). Optimization of dynamic relocation operations for one-way electric carsharing systems, Transportation Research C: Emerging Technologies 101: 55–69.
• [24] Weikl, S. and Bogenberger, K. (2015). A practice-ready relocation model for free-floating carsharing systems with electric vehicles—Mesoscopic approach and field trial results, Transportation Research C: Emerging Technologies 57: 206–223.
• [25] Yapo, P., Gupta, H. and Sorooshian, S. (1996). Automatic calibration of conceptual rainfall-runoff models: Sensitivity to calibration data, Journal of Hydrology 181(1–4): 23–48.
• [26] Yapo, P.O., Gupta, H.V. and Sorooshian, S. (1998). Multi-objective global optimization for hydrologic models, Journal of Hydrology 204(1–4): 83–97.
• [27] Yu, B., Wang, H., Song, X., Zhao, Z., Tian, Z. and Yao, B. (2020). Optimising subordinate net points layout of express enterprise with SCE–UA algorithm, Proceedings of the Institution of Civil Engineers: Transport 173(1): 51–58.

Uwagi

PL

Opracowanie rekordu ze środków MEiN, umowa nr SONP/SP/546092/2022 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2022-2023)