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

Authors

  • Mohammad Deni Akbar School of Industrial and System Engineering, Telkom University
  • Rio Aurachmana School of Industrial and System Engineering, Telkom University

DOI:

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

Keywords:

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

Abstract

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.

Author Biographies

Mohammad Deni Akbar, School of Industrial and System Engineering, Telkom University

School of Industrial and System Engineering, Telkom University

Rio Aurachmana, School of Industrial and System Engineering, Telkom University

School of Industrial and System Engineering, Telkom University

References

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Published

2020-02-29

How to Cite

Akbar, M. D., & Aurachmana, R. (2020). Hybrid genetic-tabu search algorithm to optimize the route for capacitated vehicle routing problem with time window. International Journal of Industrial Optimization, 1(1), 15–28. https://doi.org/10.12928/ijio.v1i1.1421

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Articles