Processing, Please wait...

  • Publisher Home
  • Home
  • 🔙 Back
  • 📚 Journals
    • ⚙️ IJIEC - Industrial Engineering Computations
    • 🌐 IJDNS - Data and Network Science
    • 🧪 CCL - Current Chemistry Letters
    • 💹 AC - Accounting
    • 🎯 DSL - Decision Science Letters
    • 🚛 USCM - Uncertain Supply Chain Management
    • 🏗️ JPM - Journal of Project Management
    • 🏥 HE - Healthcare Engineering
    • 📈 SCI - Scientometrica
    • 🔩 ESM - Engineering Solid Mechanics
    • 🌿 JFS - Journal of Future Sustainability
    • 💼 MSL - Management Science Letters
  • 📝 Submit Article
  • 📊 Statistics
  • 📋 About
    • 📄 About Us
    • 📰 Blog
    • 📢 News
    • 📧 Contact
  • 📺 Tutorial
  • Search:
  • Advanced Search

Growing Science » International Journal of Industrial Engineering Computations » The electric vehicle routing problem with backhauls

⭐ Highly Cited Articles

  • Jaya Algorithm
  • Rao Algorithm
  • TLBO Algorithm
  • ChatGPT and Blended Learning

Journals

  • IJIEC (840)
  • IJDS (1032)
  • DSL (759)
  • ESM (434)
  • CCL (563)
  • JPM (350)
  • AC (572)
  • JFS (106)
  • MSL (2658)
  • USCM (1104)
  • HE (54)
  • SCI (53)

IJIEC Volumes

    • ▼ Volume 17 (113)
      • Issue 1 (21)
      • Issue 2 (30)
      • Issue 3 (26)
      • Issue 4 (36)
    • ▼ Volume 16 (75)
      • Issue 1 (12)
      • Issue 2 (15)
      • Issue 3 (19)
      • Issue 4 (29)
    • ▼ Volume 15 (55)
      • Issue 1 (19)
      • Issue 2 (15)
      • Issue 3 (12)
      • Issue 4 (9)
    • ▼ Volume 14 (50)
      • Issue 1 (11)
      • Issue 2 (15)
      • Issue 3 (9)
      • Issue 4 (15)
    • ▼ Volume 13 (41)
      • Issue 1 (10)
      • Issue 2 (8)
      • Issue 3 (10)
      • Issue 4 (13)
    • ▼ Volume 12 (29)
      • Issue 1 (9)
      • Issue 2 (6)
      • Issue 3 (8)
      • Issue 4 (6)
    • ▼ Volume 11 (36)
      • Issue 1 (9)
      • Issue 2 (8)
      • Issue 3 (9)
      • Issue 4 (10)
    • ▼ Volume 10 (34)
      • Issue 1 (8)
      • Issue 2 (10)
      • Issue 3 (8)
      • Issue 4 (8)
    • ▼ Volume 9 (32)
      • Issue 1 (9)
      • Issue 2 (6)
      • Issue 3 (7)
      • Issue 4 (10)
    • ▼ Volume 8 (30)
      • Issue 1 (9)
      • Issue 2 (7)
      • Issue 3 (8)
      • Issue 4 (6)
    • ▼ Volume 7 (47)
      • Issue 1 (10)
      • Issue 2 (14)
      • Issue 3 (10)
      • Issue 4 (13)
    • ▼ Volume 6 (39)
      • Issue 1 (7)
      • Issue 2 (12)
      • Issue 3 (10)
      • Issue 4 (10)
    • ▼ Volume 5 (47)
      • Issue 1 (13)
      • Issue 2 (12)
      • Issue 3 (12)
      • Issue 4 (10)
    • ▼ Volume 4 (50)
      • Issue 1 (14)
      • Issue 2 (10)
      • Issue 3 (12)
      • Issue 4 (14)
    • ▼ Volume 3 (77)
      • Issue 1 (10)
      • Issue 2 (15)
      • Issue 3 (20)
      • Issue 4 (12)
      • Issue 5 (20)
    • ▼ Volume 2 (68)
      • Issue 1 (12)
      • Issue 2 (20)
      • Issue 3 (20)
      • Issue 4 (16)
    • ▼ Volume 1 (17)
      • Issue 1 (9)
      • Issue 2 (8)

🔑 Keywords

Jordan(175)
Supply chain management(172)
Vietnam(154)
Customer satisfaction(124)
Performance(117)
Supply chain(115)
Artificial intelligence(108)
Service quality(101)
Competitive advantage(100)
SMEs(95)
Sustainability(94)
Tehran Stock Exchange(94)
optimization(88)
Financial performance(86)
TOPSIS(85)
Trust(85)
Genetic Algorithm(81)
Organizational performance(81)
Job satisfaction(81)
Social media(80)


» Show all keywords

✍️ Authors

Naser Azad(82)
Zeplin Jiwa Husada Tarigan(70)
Mohammad Reza Iravani(65)
Endri Endri(45)
Hotlan Siagian(43)
Muhammad Alshurideh(42)
Dmaithan Almajali(39)
Jumadil Saputra(37)
Muhammad Turki Alshurideh(35)
Ahmad Makui(33)
Sautma Ronni Basana(33)
Barween Al Kurdi(32)
Basrowi Basrowi(31)
Mohammad Khodaei Valahzaghard(30)
Haitham M. Alzoubi(30)
Ni Nyoman Kerti Yasa(30)
Hassan Ghodrati(30)
Shankar Chakraborty(29)
Sulieman Ibraheem Shelash Al-Hawary(28)
Mahmoud Allahham(28)


» Show all authors

🌍 Countries

1. Algeria (52)
2. Angola (2)
3. Argentina (22)
4. Armenia (2)
5. Australia (52)
6. Austria (2)
7. Bahrain (26)
8. Bangladesh (58)
9. Belarus (4)
10. Belgium (3)
11. Benin (2)
12. Benin Republic (1)
13. Bhutan (1)
14. Bosnia and Herzegovina (1)
15. Botswana (9)
16. Brazil (40)
17. Brunei (1)
18. Bulgaria (1)
19. Burkina Faso (1)
20. Cameroon (1)
Total: 121 countries

Show all countries
International Journal of Industrial Engineering Computations
ISSN 1923-2934 (Online) - ISSN 1923-2926 (Print)
Quarterly Publication
Volume 11 Issue 1 pp. 131-152, 2020

The electric vehicle routing problem with backhauls Pages 131-152 PDF Download PDF

Authors: Mauricio Granada-Echeverri, Luis Carlos Cubides, Jésus Orlando Bustamante

📋 Author Affiliations:
Mauricio Granada-Echeverri1, Luis Carlos Cubides2, Jésus Orlando Bustamante1
1 Universidad Tecnológica de Pereira, Risaralda, Colombia
2 Information and Communication Technologies Management Audifarma SA, Pereira, Risaralda, Colombia
doi 10.5267/j.ijiec.2019.6.001
34 Source: Scopus
Crossref 24 Source: CrossRef

🔑 Keywords: Electric vehicle routing problem, Mixed integer linear programming Backhaul, Linehaul, VRPB

Abstract: In the classical vehicle routing problem with backhauls (VRPB) the customers are divided into two sets; the linehaul and backhaul customers, so that the distribution and collection services of goods are separated into different routes. This is justified by the need to avoid the reorganization of the loads inside the vehicles, to reduce the return of the vehicles with empty load and to give greater priority to the customers of the linehaul. Many logistics companies have special responsibility to make their operations greener, and electric vehicles (EVs) can be an efficient solution. Thus, when the fleet consists of electric vehicles (EVs), the driving range is limited due to their battery capacities and, therefore, it is necessary to visit recharging stations along their route. In this paper the electric vehicle routing problem with backhauls (EVRPB) is introduced and formulated as a mixed integer linear programming model. This formulation is based on the generalization of the open vehicle routing problem considering a set of new constraints focussed on maintaining the arborescence condition of the linehaul and backhaul paths. Different charging points for the EVs are considered in order to recharge the battery at the end of the linehaul route or during the course of the backhaul route. Finally, a heuristic initialization methodology is proposed, in which an auxiliary graph is used for the efficient coding of feasible solutions to the problem. The operation and effectiveness of the proposed formulation is tested on two VRPB instance datasets of literature which have been adapted to the EVRPB.

How to cite this paper
APA: Granada-Echeverri, M., Cubides, L & Bustamante, J. (2020). The electric vehicle routing problem with backhauls. International Journal of Industrial Engineering Computations, 11(1), 131-152.
Chicago/Turabian: Granada-Echeverri, M., Cubides, L & Bustamante, J. 2020. "The electric vehicle routing problem with backhauls." International Journal of Industrial Engineering Computations 11, no. 1 (2020): 131-152.
AMA: Granada-Echeverri, M., Cubides, L & Bustamante, J. The electric vehicle routing problem with backhauls. International Journal of Industrial Engineering Computations. 2020;11(1):131-152.

References
Alinaghian, M., Kalantari, M. R., Bozorgi-Amiri, A., & Raad, N. G. (2016). A novel mathematical model for cross dock open-close vehicle routing problem with splitting. Int. J. Math. Sci. Comput.(IJMSC), 2(3), 21-31.
Arias, A., Granada, M., & Castro, C. A. (2017). Optimal probabilistic charging of electric vehicles in distribution systems. IET Electrical Systems in Transportation, 7(3), 246-251.
Bodin, L. (1983). Routing and scheduling of vehicles and crews, the state of the art. Comput. Oper. Res., 10(2), 63-211.
Cattaruzza, D., Absi, N., Feillet, D., & Vidal, T. (2014). A memetic algorithm for the multi trip vehicle routing problem. European Journal of Operational Research, 236(3), 833-848.
Chávez, J., Escobar, J., & Echeverri, M. (2016). A multi-objective Pareto ant colony algorithm for the Multi-Depot Vehicle Routing problem with Backhauls. International Journal of Industrial Engineering Computations, 7(1), 35-48.
Chávez, J., Escobar, J., Echeverri, M., & Meneses, C. (2018). A heuristic algorithm based on tabu search for vehicle routing problems with backhauls. Decision Science Letters, 7(2), 171-180.
Cormen, T. H., Leiserson, C. E., Rivest, R. L., & Stein, C. (2001). Introduction to algorithms second edition. The Knuth-Morris-Pratt Algorithm, year.
Dharmakeerthi, C. H., Mithulananthan, N., & Saha, T. K. (2012, July). Modeling and planning of EV fast charging station in power grid. In 2012 IEEE Power and Energy Society General Meeting (pp. 1-8). IEEE.
Electrification Coalition (2012) EV case study, the electric drive bellwether? - FedEx express on lessons learned - From global EV deployments. Tech. rep., Washington DC.
Fisher, M. L., Jaikumar, R., & Van Wassenhove, L. N. (1986). A multiplier adjustment method for the generalized assignment problem. Management Science, 32(9), 1095-1103.
Fourer, R., Gay, D. M., & Kernighan, B. W. (1990). A modeling language for mathematical programming. Management Science, 36(5), 519-554.
Ge, S., Feng, L., & Liu, H. (2011, September). The planning of electric vehicle charging station based on grid partition method. In 2011 International Conference on Electrical and Control Engineering (pp. 2726-2730). IEEE.
Goeke, D., & Schneider, M. (2015). Routing a mixed fleet of electric and conventional vehicles. European Journal of Operational Research, 245(1), 81-99.
Goetschalckx, M., & Jacobs-Blecha, C. (1989). The vehicle routing problem with backhauls. European Journal of Operational Research, 42(1), 39-51.
Irnich, S., Schneider, M., & Vigo, D. (2014). Chapter 9: Four Variants of the Vehicle Routing Problem. In Vehicle Routing: Problems, Methods, and Applications, Second Edition (pp. 241-271). Society for Industrial and Applied Mathematics.
Koç, Ç., & Laporte, G. (2018). Vehicle routing with backhauls: Review and research perspectives. Computers & Operations Research, 91, 79-91.
Letchford, A. N., Lysgaard, J., & Eglese, R. W. (2007). A branch-and-cut algorithm for the capacitated open vehicle routing problem. Journal of the Operational Research Society, 58(12), 1642-1651.
Li, F., Golden, B., & Wasil, E. (2007). The open vehicle routing problem: Algorithms, large-scale test problems, and computational results. Computers & Operations Research, 34(10), 2918-2930.
Liu, S., Lei, L., & Park, S. (2008). On the multi-product packing-delivery problem with a fixed route. Transportation Research Part E: Logistics and Transportation Review, 44(3), 350-360.
Liu, Z., Wen, F., & Ledwich, G. (2012). Optimal planning of electric-vehicle charging stations in distribution systems. IEEE Transactions on Power Delivery, 28(1), 102-110.
Lourenco, H. R., Martin, O. C., & Stuetzle, T. (2002). Handbook of Metaheuristics, chapter Iterated local search.
Mingozzi, A., Giorgi, S., & Baldacci, R. (1999). An exact method for the vehicle routing problem with backhauls. Transportation Science, 33(3), 315-329.
Ochi, L. S., Vianna, D. S., Drummond, L. M., & Victor, A. (1998). A parallel evolutionary algorithm for the vehicle routing problem with heterogeneous fleet. Future Generation Computer Systems, 14(5-6), 285-292.
Parragh, S. N., Doerner, K. F., & Hartl, R. F. (2008). A survey on pickup and delivery problems. Journal für Betriebswirtschaft, 58(1), 21-51.
Paz, J., Granada-Echeverri, M., & Escobar, J. (2018). The multi-depot electric vehicle location routing problem with time windows. International Journal of Industrial Engineering Computations, 9(1), 123-136.
Pessoa, A., De Aragão, M. P., & Uchoa, E. (2008). Robust branch-cut-and-price algorithms for vehicle routing problems. In The vehicle routing problem: Latest advances and new challenges (pp. 297-325). Springer, Boston, MA.
Pfriem, M., & Gauterin, F. (2013, November). Less range as a possible solution for the market success of electric vehicles in commercial fleets. In 2013 World Electric Vehicle Symposium and Exhibition (EVS27) (pp. 1-8). IEEE.
Prins, C. (2004). A simple and effective evolutionary algorithm for the vehicle routing problem. Computers & Operations Research, 31(12), 1985-2002.
Ropke, S., & Pisinger, D. (2006). A unified heuristic for a large class of vehicle routing problems with backhauls. European Journal of Operational Research, 171(3), 750-775.
Salari, M., Toth, P., & Tramontani, A. (2010). An ILP improvement procedure for the open vehicle routing problem. Computers & Operations Research, 37(12), 2106-2120.
Schrage, L. (1981). Formulation and structure of more complex/realistic routing and scheduling problems. Networks, 11(2), 229-232.
Stützle, T. (1999). Local search algorithms for combinatorial problems-analysis, algorithms and new applications. DISKI-Dissertationen zur Künstliken Intelligenz. In x, Sankt Augustin, Germany.
Taillard, É. (1993). Parallel iterative search methods for vehicle routing problems. Networks, 23(8), 661-673.
Toro, E. M., Franco, J. F., Echeverri, M. G., & Guimarães, F. G. (2017a). A multi-objective model for the green capacitated location-routing problem considering environmental impact. Computers & Industrial Engineering, 110, 114-125.
Toro, E., Franco, J., Echeverri, M., Guimarães, F., & Rendón, R. (2017b). Green open location-routing problem considering economic and environmental costs. International Journal of Industrial Engineering Computations, 8(2), 203-216.
Toth, P., & Vigo, D. (1997). An exact algorithm for the vehicle routing problem with backhauls. Transportation science, 31(4), 372-385.
Toth, P., & Vigo, D. (Eds.). (2002). The vehicle routing problem. Society for Industrial and Applied Mathematics.
Toth, P., & Vigo, D. (Eds.). (2014). Vehicle routing: problems, methods, and applications. Society for Industrial and Applied Mathematics.
Van Breedam, A. (1994). An Analysis of the Behavior of Heuristics for the Vehicle Routing Problem for a Selectrion of Problems with Vehicle-related, Customer-related, and Time-related Constraints. RUCA.
Vidal, T., Crainic, T. G., Gendreau, M., Lahrichi, N., & Rei, W. (2012). A hybrid genetic algorithm for multidepot and periodic vehicle routing problems. Operations Research, 60(3), 611-624.
Wade, A., & Salhi, S. (2003). An ant system algorithm for the mixed vehicle routing problem with backhauls. In Metaheuristics: computer decision-making (pp. 699-719). Springer, Boston, MA.
Wang, G., Xu, Z., Wen, F., & Wong, K. P. (2013). Traffic-constrained multiobjective planning of electric-vehicle charging stations. IEEE Transactions on Power Delivery, 28(4), 2363-2372.
Yang, J., & Sun, H. (2015). Battery swap station location-routing problem with capacitated electric vehicles. Computers & Operations Research, 55, 217-232.
  • 0
  • 1
  • 2
  • 3
  • 4
  • 5

📚 Journal: International Journal of Industrial Engineering Computations | 📅 Year: 2020 | 📖 Volume: 11 | 📄 Issue: 1 | 👁️ Views: 3600 | 📊 Crossref: 24

Related Articles:
  • A mixed integer linear programming formulation for the vehicle routing problem with backhauls
  • Variable neighborhood search algorithm for the green vehicle routing problem
  • A heuristic algorithm based on tabu search for vehicle routing problems with backhauls
  • The multi-depot electric vehicle location routing problem with time windows
  • A multi-objective Pareto ant colony algorithm for the Multi-Depot Vehicle Routing problem with Backhauls

📝 Ready to share your research?

International Journal of Industrial Engineering Computations is accepting new submissions for upcoming issues. Join our community of authors and publish your work with us.

✓ Open access
✓ Rigorous peer review
✓ Fast publication
📤 Submit Your Manuscript →

📖 Author Guidelines

® 2010-2026 GrowingScience.Com