Design of Feed Product Distribution System using Vehicle Routing Problem (VRP) and Simulated Annealing (SA) Methods at XYZ, L.P

Authors

  • I.K. Sriwana Dept. of Industrial Engineering, Telkom University, Bandung 40257 Indonesia
  • N. Syauqillah Dept. of Industrial Engineering, Esa Unggul University, Jakarta 11510 Indonesia
  • N. Erni Dept. of Industrial Engineering, Esa Unggul University, Jakarta 11510 Indonesia
  • R. Rasjidin Dept. of Industrial Engineering, Esa Unggul University, Jakarta 11510 Indonesia
  • Taufiqur Rachman Dept. of Industrial Engineering, Esa Unggul University, Jakarta 11510 Indonesia

DOI:

https://doi.org/10.15282/jmmst.v6i1.6910

Keywords:

Vehicle Routing Problem, Nearest Neighbor, Simulated Annealing

Abstract

A good distribution system can give an impact on cost efficiency and delivery time. XYZ , L.P is an animal feed firm who faces problems of high cost and long time to carry out distribution activities. This happens after an increase in demand for animal feed which was not followed by significance of increase in cost and distribution time. The research aimed to design a distribution system and determine an optimum distribution route using efficient resources, in order to obtain a minimum vehicle mileage. The research consists of 8 stages. Vehicle Routing Problem (VRP) with Nearest Neighbor method was carried out, followed by optimizing the route solution obtained from the VRP calculation using the Simulated Annealing (SA) Algorithm. According to the route optimization using SA, the mileage, travel time, and distribution costs can be reduced by 40.04%, 75%, and 49.85%, respectively. It is, therefore, assumed that the firm can gain benefits, in terms of cost and time, by implementing the proposed distribution method.

References

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Published

2022-03-31

How to Cite

Sriwana, I., Syauqillah, N., Erni, N., Rasjidin, R., & Rachman, T. (2022). Design of Feed Product Distribution System using Vehicle Routing Problem (VRP) and Simulated Annealing (SA) Methods at XYZ, L.P. Journal of Modern Manufacturing Systems and Technology, 6(1), 23–31. https://doi.org/10.15282/jmmst.v6i1.6910

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