PENYELESAIAN CAPACITATED VEHICLE ROUTING PROBLEM (CVRP) DENGAN EVOLUTIONARY ALGORITHM & EXCEL SOLVER (STUDI KASUS: RUSSIA-20-NODES-CVRP INSTANCE)

Ekra Sanggala

Abstract


CVRP merupakan masalah paling sederhana dari VRP. Evolutionary Algorithm (EA) merupakan sebuah metaheuristic yang dapat diaplikasikan pada berbagai permasalahan optimasi, termasuk CVRP. Solver merupakan Excel Add-In untuk menyelesaikan permasalahan optimasi. Solver menggunakan tiga algoritma, yaitu LP Simplex, GRG Nonlinear dan EA. Dengan adanya kemampuan EA untuk menyelesaikan CVRP dan Solver yang mampu menjalankan EA, maka dapat disimpulkan bahwa penyelesaian CVRP dapat dilakukan dengan memanfaatkan Solver. Russia-20-Nodes-CVRP Instance merupakan salah satu CVRP Instance yang terdapat pada Russian CVRP Instances. Dengan menggunakan EA & Solver, panjang rute terpendek dari Russia-20-Nodes-CVRP Instance adalah 15.884 Km.

Keywords


CVRP, Evolutionary Algorithm, Excel Solver, CVRP Instance

References


Badar, A. Q. H. (2021). Evolutionary Optimization Algorithms. CRC Press.

Elshaer, R., & Awad, H. (2020). A taxonomic review of metaheuristic algorithms for solving the vehicle routing problem and its variants. Computers & Industrial Engineering, 140, 106242.

Golden, B., Wang, X., & Wasil, E. (2023). The Evolution of the Vehicle Routing Problem—A Survey of VRP Research and Practice from 2005 to 2022. In The Evolution of the Vehicle Routing Problem: A Survey of VRP Research and Practice from 2005 to 2022 (pp. 1–64). Springer.

Idrizi, B. (2020). Necessity for geometric corrections of distances in web and mobile maps. International Conference on Cartography and GIS, Bulgaria.

Janga Reddy, M., & Nagesh Kumar, D. (2020). Evolutionary algorithms, swarm intelligence methods, and their applications in water resources engineering: a state-of-the-art review. H2oj, 3(1), 135–188.

Sanggala, E., & Bisma, M. A. (2023). Analysis of The Badar, A. Q. H. (2021). Evolutionary Optimization Algorithms. CRC Press.

Elshaer, R., & Awad, H. (2020). A taxonomic review of metaheuristic algorithms for solving the vehicle routing problem and its variants. Computers & Industrial Engineering, 140, 106242.

Golden, B., Wang, X., & Wasil, E. (2023). The Evolution of the Vehicle Routing Problem—A Survey of VRP Research and Practice from 2005 to 2022. In The Evolution of the Vehicle Routing Problem: A Survey of VRP Research and Practice from 2005 to 2022 (pp. 1–64). Springer.

Idrizi, B. (2020). Necessity for geometric corrections of distances in web and mobile maps. International Conference on Cartography and GIS, Bulgaria.

Janga Reddy, M., & Nagesh Kumar, D. (2020). Evolutionary algorithms, swarm intelligence methods, and their applications in water resources engineering: a state-of-the-art review. H2oj, 3(1), 135–188.

Sanggala, E., & Bisma, M. A. (2023). Analysis of The Ant Number Effects on Ant Colony Optimization for Solving Russia-20-Nodes-SDVRP Instance. Sainteks: Jurnal Sain Dan Teknik, 5(2), 163–174.

Selvi, A. A., Selvabharathi, S. M., & Lavanya, S. (2022). Real Life Optimization Problem using Excel and Solver. International Journal of Research in Engineering, Science and Management, 5(5), 155–157.

Tan, S.-Y., & Yeh, W.-C. (2021). The vehicle routing problem: State-of-the-art classification and review. Applied Sciences, 11(21), 10295.




DOI: https://doi.org/10.33373/profis.v11i2.5896

Refbacks

  • There are currently no refbacks.


Copyright (c) 2023 PROFISIENSI: Jurnal Program Studi Teknik Industri

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

E-ISSN 2598-9987

 

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


PROFISIENSI: Jurnal Program Studi Teknik Industri

Building A, 1st Floor, Faculty of Engineering, University of Riau Kepulauan

Jl. Pahlawan No.99, Batu Aji, Batam, Kepulauan Riau

Email: Profisiensi@journal.unrika.ac.id

 

Web Analytics Made Easy - Statcounter