Hybrid genetic–tabu search algorithm to optimize the route for capacitated vehicle routing problem with time window

Mohammad Deni Akbar, Rio Aurachmana


Optimization of transportation and distribution costs is one of the important issues in the supply chain management area. It is caused by their large contribution to the logistics costs that can reach up to 40%. Thus, choosing the right route is one of the efforts that can be done to resolve the issue. This study aims to optimize the capacitated vehicle routing problem with time windows (CVRPTW) for mineral water company distributor with pick-up and delivery problem. To achieve the aim, this study used hybrid algorithm, Genetic Algorithm (GA) and Tabu Search Algorithm (TS). The selection of this hybrid algorithm is due to its capability in minimizing travel distance. The result of this study shows that not only the algorithm has successfully reduced the existing route but also predicted the optimum number of homogenous fleet. By running the algorithm, this study concludes that the number of the optimum routes for this study can be reduced for up to 15.99% than the existing route.


Genetic Algorithm; Tabu Search; Capacitated Vehicle Routing Problem with Time Windows; Pick-up and Delivery

Full Text:



Abdurrahman, A. F., Ridwan, A. Y., & Santosa, B. (2018). Completion Vehicle Routing Problem (Vrp) In Determining Route And Determining The Number Of Vehicles In Minimizing Transportation Costs In PT. XYZ With Using Genetic Algorithm. International Journal of Innovation in Enterprise System, 2(02), 24-30.

Baker, B. M., & Ayechew, M. A. (2003). A genetic algorithm for the vehicle routing problem. Computers & Operations Research, 30(5), 787-800.

Brilliane, C. S., Ridwan, A. Y., & Aurachman, R. (2019). Designing Route Distribution Using Two Phase Tabu Search On Heterogenous Fleet Vehicle Routing Problem With Time Window In Pt. Xyz To Minimize Travel Distance. International Journal of Innovation in Enterprise System, 3(01), 6-14.

Crainic, T. G., & Laporte, G. (Eds.). (2012). Fleet management and logistics. Springer Science & Business Media.

Frazelle, E. (2002). Supply chain strategy: the logistics of supply chain management. McGrraw Hill.

Hugos, M. H. (2018). Essentials of supply chain management. John Wiley & Sons.

Lai, D. S., Demirag, O. C., & Leung, J. M. (2016). A tabu search heuristic for the heterogeneous vehicle routing problem on a multigraph. Transportation Research Part E: Logistics and Transportation Review, 86, 32-52.

Lu, D. (2011). Fundamentals of supply chain management. Bookboo

Mak, K. L., & Sun, D. (2009). A new hybrid genetic algorithm and tabu search method for yard cranes scheduling with inter-crane interference. In Proceedings of the World Congress on Engineering 2009. Newswood Limited..

Mohammed, M. A., Ghani, M. K. A., Hamed, R. I., Mostafa, S. A., Ahmad, M. S., & Ibrahim, D. A. (2017). Solving vehicle routing problem by using improved genetic algorithm for optimal solution. Journal of Computational Science, 21, 255-262.

Sonawane, M. P. A., & Ragha, L. (2014). Hybrid genetic algorithm and TABU search algorithm to solve class time table scheduling problem. International Journal of Research Studies in Computer Science and Engineering, 1(4), 19-26.

Toth, P., & Vigo, D. (1998). Exact solution of the vehicle routing problem. In Fleet management and logistics (pp. 1-31). Springer, Boston, MA.

Toth, P., & Vigo, D. (2002). An overview of vehicle routing problems. In The vehicle routing problem (pp. 1-26). Society for Industrial and Applied Mathematics.

Toth, P., & Vigo, D. (Eds.). (2014). Vehicle routing: problems, methods, and applications. Society for Industrial and Applied Mathematics.

Utamima, A., Pradina, K. R., Dini, N. S., & Studiawan, H. (2015). Distribution route optimization of gallon water using genetic algorithm and tabu search. Procedia Computer Science, 72, 503-510.

DOI: https://doi.org/10.12928/ijio.v1i1.1421


  • There are currently no refbacks.

Copyright (c) 2020 Mohammad Deni Akbar, Rio Aurachmana

Creative Commons License
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.


International Journal of Industrial Optimization (IJIO)
ISSN: 2714-6006, e-ISSN: 2723-3022
Universitas Ahmad Dahlan, 4th Campus
Jl. Ringroad Selatan, Kragilan, Tamanan, Banguntapan, Bantul, Yogyakarta, Indonesia 55191
Phone: +62 (274) 563515, 511830, 379418, 371120 ext. 4902, Fax: +62 274 564604

View IJIO Stats