TELKOMNIKA Telecommunication, Computing, Electronics and Control
Sensitivity of shortest distance search in the ant colony algorithm with varying normalized distance formulas

TELKOMNIKA Telecommunication, Computing, Electronics and Control
Sensitivity of shortest distance search in the ant colony algorithm with varying normalized distance formulas

Ant colony
Normalized distance
Optimization
Searching

The ant colony algorithm is an algorithm adopted from the behavior of ants
which naturally ants are able to find the shortest route on the way from the nest
to places of food sources based on footprints on the track that has been passed.
The ant colony algorithm helps a lot in solving several problems such as
scheduling, traveling salesman problems (TSP) and vehicle routing problems
(VRP). In addition, ant colony has been developed and has several variants.
However, in its function to find the shortest distance is optimized by utilizing
several normalized distance formulas with the data used in finding distances
between merchants in the mercant ecosystem. Where in the test normalized
distance is superior Hamming distance in finding the shortest distance of
0.2875, then followed by the same value, namely the normalized formula
Manhattan distance and normalized Euclidean distance with a value of 0.4675
and without using the normalized distance formula or the original ant colony
algorithm gets a value 0.6635. Given the sensitivity in distance search using
merchant ecosystem data, the method works well on the ant colony Algorithm
using normalized Hamming distance.

Rahmad Syah, Mahyuddin K. M. Nasution, Erna Budhiarti Nababan, Syahril Efendi

http://journal.uad.ac.id/index.php/TELKOMNIKA

Mar 19, 2021

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