SEARCHING OPTIMUM ROUTE USE ANT COLONY OPTIMIZATION WITH ASISSTED GOOGLE API

Martono, Alvin Ariyanto (2016) SEARCHING OPTIMUM ROUTE USE ANT COLONY OPTIMIZATION WITH ASISSTED GOOGLE API. Other thesis, Fakultas Ilmu Komputer UNIKA Soegijapranata Semarang.

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Abstract

The route want to destination point have many possibility route, so one must to find the best route so there would not be any wasted energy, money and time. For traveling for works furthermore, saving time and money is really important. So if there could be a way to automatically find the most optimal route to take it would definitely be a life saver. This program uses Ant Colony Optimization Algorithm to find the optimal route because it could give the best result from departure city until destination point. The Ant Colony Optimization adoption from how real life ants find their food, how the colony of ant first spread around to search for food from their nest, and when one of the ant found some food it would inform the others to follow the path to get the food. In programming world Ant Colony Optimization has a concept that every city has a value, then the ant colony algorithm optimization would create a random value from these cities inputed, which then would be compared to the values of each cities. When there was a value close to that random value, the city with that value would be taken out and chosen as the next destination. This program would continue this until every city has been put into a chronological order. The result from this is a list of the most optimal route to go from the departure city to the destinations through the cities included in the route wanted. With the assistance of Google Api it would also have visualized map with colorized routes and distances between each routes and cities.

Item Type:	Thesis (Other)
Subjects:	000 Computer Science, Information and General Works > 004 Data processing & computer science
Divisions:	Faculty of Computer Science > Department of Informatics Engineering
Depositing User:	Mr Ign. Setya Dwiana
Date Deposited:	31 May 2016 06:23
Last Modified:	18 Nov 2022 06:30
URI:	http://repository.unika.ac.id/id/eprint/9715

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