Aplikasi Pencari Rute Optimum Menggunakan Algoritma Semut di Kampus Universitas Sumatera Utara dengan Dukungan Sistem Informasi Geografis
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Institusion
Universitas Sumatera Utara
Author
Purba, Friendly (STUDENT ID : 061401039)
(LECTURER ID : 0010116706)
(LECTURER ID : 0008107507)
(LECTURER ID : 0010116706)
(LECTURER ID : 0008107507)
Subject
Shortest Path Problem
Datestamp
2022-12-14 06:50:36
Abstract :
The shortest path searching generally can be divided into two methods, both are conventional methods and heuristic methods. Heuristic methods are more suitable than the conventional methods in finding the shortest path with large data. Heuristic method that is often used in determining the shortest path is the Ant Algorithm. Ant Algorithm is adopted from the natural behavior of ants that makes finding the shortest path is faster even when working with large data. After doing examination to every Ant Algorithm parameters, we conclude that parameters number of ants and many cycles affect the probability of getting the destination point and the time execution of searching optimum path, parameters ?ij, q0 and ? affect the probability of getting the destination point, while parameters ? and ? affect the time execution of searching optimum path. This optimum path searching application that implements the ant algorithm is built using Geographic Information System software MapWindow and Delphi 2009 that is expected to provide enough useful information for road users at the University of Sumatera Utara.
The shortest path searching generally can be divided into two methods, both are conventional methods and heuristic methods. Heuristic methods are more suitable than the conventional methods in finding the shortest path with large data. Heuristic method that is often used in determining the shortest path is the Ant Algorithm. Ant Algorithm is adopted from the natural behavior of ants that makes finding the shortest path is faster even when working with large data. After doing examination to every Ant Algorithm parameters, we conclude that parameters number of ants and many cycles affect the probability of getting the destination point and the time execution of searching optimum path, parameters ?ij, q0 and ? affect the probability of getting the destination point, while parameters ? and ? affect the time execution of searching optimum path. This optimum path searching application that implements the ant algorithm is built using Geographic Information System software MapWindow and Delphi 2009 that is expected to provide enough useful information for road users at the University of Sumatera Utara.
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