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

Authors

  • Ekra Sanggala Universitas Logistik dan Bisnis Internasional

DOI:

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

Keywords:

CVRP, Evolutionary Algorithm, Excel Solver, CVRP Instance

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.

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.

Published

2023-12-31