The Application of Genetic Algorithm in Solving Traveling Salesman Problem

Elis Wulan; Neulis Apriani

Proceedings of the 1st International Conference on Islam, Science and Technology, ICONISTECH 2019, 11-12 July 2019, Bandung, Indonesia.

Research Article

The Application of Genetic Algorithm in Solving Traveling Salesman Problem

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@INPROCEEDINGS{10.4108/eai.11-7-2019.2297522,
    author={Elis Ratna Wulan and Neulis Pipit Apriani},
    title={The Application of Genetic Algorithm in Solving Traveling Salesman Problem},
    proceedings={Proceedings of the 1st International Conference on Islam, Science and Technology, ICONISTECH 2019, 11-12 July 2019, Bandung, Indonesia.},
    publisher={EAI},
    proceedings_a={ICONISTECH},
    year={2021},
    month={1},
    keywords={traveling salesman problem (tsp) optimization genetic algorithm},
    doi={10.4108/eai.11-7-2019.2297522}
}

Elis Ratna Wulan
Neulis Pipit Apriani
Year: 2021
The Application of Genetic Algorithm in Solving Traveling Salesman Problem
ICONISTECH
EAI
DOI: 10.4108/eai.11-7-2019.2297522

Elis Ratna Wulan¹^,*, Neulis Pipit Apriani¹

1: Mathematics Department, Science and Technology Faculty, UIN Sunan Gunung Djati Bandung, Indonesia

*Contact email: elis_ratna_wulan@uinsgd.ac.id

Abstract

Traveling Salesman Problem (TSP) is one form of optimization problem with easy concept, but complicated if solved conventionally. The purpose of TSP is to build an optimal routes, with the rules of each city to be visited by salesmen and the cities are visited only exactly once, the trip begins and ends in the city early. To build the optimal routes, in this study using genetic algorithm. In the example case there are 4 cities that must be traversed by the salesman, that city A, B, C, and D with the trip starts from the city A and ends in city A as well. So obtained the optimal route that is [A D B C] with minimum distance that is 19 km.

Keywords: traveling salesman problem (tsp) optimization genetic algorithm

Published: 2021-01-12
Publisher: EAI

: http://dx.doi.org/10.4108/eai.11-7-2019.2297522