The best route determination using nearest neighbor approach

Authors

  • Nafia Rahma Universitas Ahmad Dahlan
  • Annie Purwani Universitas Ahmad Dahlan
  • Dwi Nita Febriyanto Universitas Ahmad Dahlan

DOI:

https://doi.org/10.12928/ijio.v1i1.1423

Keywords:

Nearest neighbor, Heuristic optimization, Garbage freight, Route determination, Operational time

Abstract

This research constitutes an application of heuristic optimization using the nearest neighbor (NN) method. It is a method used to design a route based on the next closest distance. The case here is the garbage freight of Yogyakarta City which becomes one of the Environmental Services Department duties. The sector of this research object is Malioboro-Kranggan because it has the highest number of TPS locations. There are 34 TPS locations, and 2 depots with an average volume of total garbage are 197 m3/day. Several alternative routes have resulted because the same distance was found when deciding the next distance (TPS 26 and TPS 31). The best alternative was determined based on the best scenario parameter of total mileage and operational time. The first scenario chose the garbage volume that is close to the remaining capacity, meanwhile, the second scenario chose the smallest garbage volume. At TPS 27, an alternative with the same closest distance appeared again (TPS 15 and TPS 18). Hence, the whole algorithm results in four alternative decisions. The first alternative results 13.59 hours as the total time and 40.092 km as the total distance, the second results 13.50 hours with 40.315 km, the third results 13.57 hours with 41.393 km, and the fourth results 13.803 hours with 40.41 km. The best alternative goes to the first alternative based on the parameter set before. It means that the scenario taken is by choosing the TPS with the closest remaining volume of the vehicle.

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Published

2020-02-29

How to Cite

Rahma, N., Purwani, A., & Febriyanto, D. N. (2020). The best route determination using nearest neighbor approach. International Journal of Industrial Optimization, 1(1), 43–52. https://doi.org/10.12928/ijio.v1i1.1423

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Articles