Systematic Literature Review of GPS-based Multi-Objective Environmentally Friendly Shortest Path with a Proposed Lexicographic Framework

Thania Nur Salsabila, Diah Chaerani, Herlina Napitupulu

Abstract


Environmentally friendly path planning has become an important topic in transportation research as concerns about carbon emissions continue to grow. This study aims to review existing research on environmentally friendly shortest path problems and to identify the current state of the art in green shortest path optimization. A Systematic Literature Review is conducted using the PRISMA guideline and supported by bibliometric analysis to examine research trends and optimization methods discussed in the literature. The review indicates that most studies focus on metaheuristic and artificial intelligence–based approaches, while deterministic methods with explicit objective prioritization receive less attention. Based on the synthesis of previous studies, this paper discusses emerging research directions and outlines a conceptual framework for priority-based multi-objective shortest path optimization. The results of this review provide a clear overview of current methods and can support future research on eco-friendly shortest path models.


Keywords


Green shortest path; Multi-objective shortest path problem; Lexicographic method; Systematic literature review; Transportation network

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References


S. S. Rao, Engineering Optimization: Theory and Practice, 5th. Hoboken, NJ: John Wiley & Sons, 2020.

H. Napitupulu, E. Carnia, N. Anggriani, and A. K. Supriatna, “Centrality measures in transportation networks for unpad campus route,” Journal of Physics: Conference Series, vol. 1722, no. 1, p. 012063, 2021. doi: 10.1088/1742-6596/1722/1/012063

J. Current and M. Marsh, “Multiobjective transportation network design and routing problems: Taxonomy and annotation,” European Journal of Operational Research, vol. 65, no. 1, pp. 4–19, 1993. doi: 10.1016/0377-2217(93)90140-I.

C. C. Azis, D. Chaerani, and E. Rusyaman, “Analysis of multi-objective linear robust optimization model with lexicographical method,” Media Statistika, vol. 17, no. 1, pp. 57–68, 2024. doi: 10.14710/medstat.17.1.57-68.

D. Chaerani, S. R. Adawiyah, and E. Lesmana, “Robust optimization model for bi-objective emergency medical service design problem with demand uncertainty,” Jurnal Teknik Industri, vol. 20, no. 2, pp. 95–104, 2018. doi: 10.9744/jti.20.2.95-104

K. Thakur, S. Maity, P. Nielsen, T. Pal, and M. Maiti, “A 3d multiobjective multi item eco-routing problem for refrigerated fresh products delivery using NSGA-II with hybrid chromosome,” Computers & Industrial Engineering, vol. 198, p. 110644, 2024. doi: 10.1016/j.cie.2024.110644.

A. Mahmoodi, L. Hashemi, J. Laliberte, and S. M. Sajadi, “Optimizing energy and CO2 efficiency in last-mile delivery using hybrid fleet models,” Sustainable Futures, vol. 10, p. 101089, 2025. doi: 10.1016/j.sftr.2025.101089.

H. Sun, M. He, Y. Gai, and J. Cao, “Optimization of fresh food logistics routes for heterogeneous fleets in segmented transshipment mode,” Mathematics, vol. 12, no. 23, p. 3831, 2024. doi: 10.3390/math12233831.

A. Sabet and B. Farooq, “Exploring the combined effects of major fuel technologies, eco routing, and eco-driving for sustainable traffic decarbonization in downtown toronto,” Transportation Research Part A: Policy and Practice, vol. 192, p. 104385, 2025. doi: 10.1016/j.tra.2025.104385.

S. M. Nasution, E. Husni, K. Kuspriyanto, and R. Yusuf, “Heterogeneous traffic condition dataset collection for creating road capacity value,” Big Data and Cognitive Computing, vol. 7, no. 1, p. 40, 2023. doi: 10.3390/bdcc7010040.

Institute for Essential Services Reform (IESR). “Wilayah perkotaan di pulau jawa menjadi kontributor tertinggi emisi karbon individu,” IESR, Accessed: Dec. 5, 2025. Available online.

A. W. Deendarlianto, T. Widodo, I. Handika, I. C. Setiawan, and A. Lindasista, “Modelling of indonesian road transport energy sector in order to fulfill the national energy and oil reduction targets,” Renewable Energy, vol. 146, no. 2, pp. 504–518, 2020. doi: 10.1016/j .renene.2019.06.169.

Kementerian Lingkungan Hidup dan Kehutanan Republik Indonesia, “Long-term strategy for low carbon and climate resilience 2050,” United Nations Framework Convention on Climate Change (UNFCCC), 2021. Accessed: Dec. 10, 2025. Available online.

B. Kitchenham and S. Charters, “Guidelines for performing systematic literature reviews in software engineering,” Keele University and Durham University, Keele, UK, Technical Report EBSE 2007-001, 2007, Joint Report.

D. Moher, A. Liberati, J. Tetzlaff, and D. G. Altman, “Preferred reporting items for systematic reviews and meta-analyses: The PRISMA statement,” Annals of Internal Medicine, vol. 151, no. 4, pp. 264–269, Aug. 2009, Epub 2009 Jul 20. doi: 10.7326/0003 4819-151-4-200908180-00135.

A. Pritchard, “Statistical bibliography or bibliometrics,” Journal of Documentation, vol. 25, no. 4, pp. 348–349, 1969.

N. Donthu, S. Kumar, D. Mukherjee, N. Pandey, and W. M. Lim, “How to conduct a bibliometric analysis: An overview and guidelines,” Journal of Business Research, vol. 133, pp. 285–296, 2021. doi: 10.1016/j.jbusres.2021.04.070

N. J. Van Eck and L. Waltman. "Software survey: VOSviewer, a computer program for bibliometric mapping," Scientometrics, vol. 84, no. 2, pp. 523–538, 2010. doi: 10.1007/s1 1192-009-0146-3.

Marsudi, Teori Graf. Malang: UB Press, 2016.

J. Hickman, D. Hassel, R. Joumard, Z. Samaras, and S. Sorenson, “Methodology for calculating transport emissions and energy consumption,” Transport Research Laboratory, Tech. Rep., 1999.

E. Demir, T. Bektas, and G. Laporte, “A review of recent research on green road freight transportation,” European Journal of Operational Research, vol. 229, no. 3, pp. 775–793, 2013. doi: 10.1016/j.ejor.2013.12.033.

A. Schrijver, Combinatorial Optimization. Springer, 2017.

Google Maps Platform, Directions api documentation, Accessed: 2025, 2024. Available online.

S. Mitchell, M. O’Sullivan, and I. Dunning, “PuLP: A linear programming toolkit for python,” The University of Auckland, Auckland, New Zealand, Tech. Rep., 2011, Report number: 65.

I. Zupic and T. Ćater, “Bibliometric methods in management and organization,” Organiza tional Research Methods, vol. 18, no. 3, pp. 429–472, 2015. doi: 10.1177/10944281145626 29.

M. E. Falagas, E. I. Pitsouni, G. A. Malietzis, and G. Pappas, “Comparison of PubMed, Scopus, Web of Science, and Google Scholar: Strengths and weaknesses,” The FASEB Journal, vol. 22, no. 2, pp. 338–342, 2008. doi: 10.1096/fj.07-9492LSF.

V. Pradeep, R. Khemmar, and F. Jendoubi, “Visual eco-routing (VER): XGBoost based eco-route selection from road scenes and vehicle emissions,” IEEE Access, vol. 12, pp. 9669 9681, 2024. doi: 10.1109/ACCESS.2024.3353036.

A. Elgammal, “Integrated path planning and speed control for electric vehicles using MOPSO-based optimization,” International Journal of Innovative Science and Research Technology, vol. 10, no. 5, 2025. doi: 10.38124/ijisrt/25may1547.

C. Zhu and X. Zhu, “Multi-objective path-decision model of multimodal transport consid ering uncertain conditions and carbon emission policies,” Symmetry, vol. 14, no. 2, p. 221, 2022. doi: 10.3390/sym14020221.

X. Yang and H. Jiang, “Research on urban cold chain logistics path optimization considering multi-center and time-varying road networks,” IEEE Access, vol. 12, pp. 71331–71348, 2024. doi: 10.1109/ACCESS.2024.3402833.

L. Li, H. Liang, J. Wang, J. Yang, and Y. Li, “Online routing for autonomous vehicle cruise systems with fuel constraints,” Journal of Intelligent & Robotic Systems, vol. 104, no. 4, p. 68, 2022. doi: 10.1007/s10846-021-01530-y.

D. Saxena et al., “An intelligent multi-depot vehicle routing and management model for smart cities,” IEEE Transactions on Intelligent Transportation Systems, vol. 26, no. 6, pp. 7740–7754, 2025. doi: 10.1109/TITS.2025.3557826.

L. Yang, C. Zhang, and X. Wu, “Multi-objective path optimization of highway-railway multimodal transport considering carbon emissions,” Applied Sciences, vol. 13, no. 8, p. 4731, 2023. doi: 10.3390/app13084731.

J. Wu, Q. Luo, and Y. Zhou, “Modified dung beetle optimizer with multi-strategy for uncertain multi-modal transport path problem,” Journal of Computational Design and Engineering, vol. 11, no. 4, pp. 40–72, 2024. doi: 10.1093/jcde/qwae058.

F. Cheng and S. Jia, “Improved GA-LNS algorithm for solving vehicle path problems considering carbon emissions,” Applied Sciences, vol. 14, no. 21, p. 9956, 2024. doi: 10.33 90/app14219956.

Y. Benmessaoud, L. Cherrat, and M. Ezziyyani, “Real-time self-adaptive traffic management system for optimal vehicular navigation in modern cities,” Computers, vol. 12, no. 4, p. 80, 2023. doi: 10.3390/computers12040080.

C. Qi, “Multi-objective optimization-based algorithm for selecting the optimal path of rural multi-temperature zone cold chain dynamic logistics intermodal transportation,” International Journal of Computational Intelligence Systems, vol. 17, no. 1, p. 224, 2024. doi: 10.1007/s44196-024-00616-3.

Q. Linyi, “Research on path selection system based on green transportation,” in E3S Web of Conferences, EILCD, Ed., vol. 275, EDP Sciences, 2021, p. 02043. doi: 10.1051/e3sco nf/202127502043. Available online.

N. Yin, “Research on green logistics distribution path based on genetic algorithm,” Procedia Computer Science, vol. 261, pp. 1036–1042, 2025. doi: 10.1016/j.procs.2025.04.682.

C. Ren et al., “Logistics distribution path optimization considering carbon emissions and multifuel-type vehicles,” Journal of Advanced Transportation, vol. 2025, p. 6668589, 2025. doi: 10.1155/ATR/6668589.

Y. Zhang, G. Shi, and J. Liu, “Dynamic energy-efficient path planning of unmanned surface vehicle under time-varying current and wind,” Journal of Marine Science and Engineering, vol. 10, no. 6, p. 759, 2022. doi: 10.3390/jmse10060759.

X. Hu, K. Hu, D. Tao, Y. Zhong, and Y. Han, “GIS-data-driven efficient and safe path planning for autonomous ships in maritime transportation,” Electronics, vol. 12, no. 10, p. 2206, 2023. doi: 10.3390/electronics12102206.

X. Lu, J. Wang, C. W. Yuen, and Q. Liu, “Multi-objective intercity carpooling route optimization considering carbon emission,” Sustainability, vol. 15, no. 3, p. 2261, 2023. doi: 10.3390/su15032261.

A. A. Ibrahim, D. Leite, and C. De Bacco, “Sustainable optimal transport in multilayer networks,” Physical Review E, vol. 105, no. 6, p. 064302, 2022. doi: 10.1103/PhysRevE.1 05.064302.

W. Xu, Q. Liu, M. Chen, and H. Zeng, “Ride the tide of traffic conditions: Opportunistic driving improves energy efficiency of timely truck transportation,” IEEE Transactions on Intelligent Transportation Systems, vol. 24, no. 5, pp. 4777–4793, 2023. doi: 10.1109 /TITS.2023.3244757.

Y. Kisialiou, A. Rialland, and V. Gribkovskaia, “Ship model-based route optimisation for decision support in deep sea shipping,” in Journal of Physics: Conference Series, vol. 2867, IOP Publishing, 2024, p. 012012. doi: 10.1088/1742-6596/2867/1/012012




DOI: https://doi.org/10.18860/cauchy.v11i1.40489

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