Skripsi

PENCARIAN RUTE TERPENDEK UNTUK PENGIRIMAN BARANG DI KOTA PALEMBANG MENGGUNAKAN ALGORITMA GENETIKA

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Penilaian

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Finding the shortest route in delivering is an important aspect in logistics efficiency, especially in urban environments such as Palembang City. Genetic algorithm was chosen due to its flexibility in handling optimization problems involving many variables. The research was conducted by varying the values of genetic algorithm parameters such as population size, iterations, crossover rate, and mutation rate to conduct a series of experiments and analyze the results obtained. Each parameter affects the performance of the genetic algorithm which shows that proper adjustment of the parameters significantly affects the efficiency of the solution search. The analysis results show that the optimal combination of parameters, such as population size of 50, number of iterations of 500, crossover rate of 80%, and mutation rate of 1%. In the context of testing with various numbers of locations, it was found that the genetic algorithm was able to provide an adequate solution with a low error value of 0,15 for 6 locations, then 0,21 for 11 locations and 0,23 for 16 locations. This error rate indicates high accuracy, offering a good solution for improving delivery efficiency. The error value is calculated based on the comparison between the estimated distance using the genetic algorithm and the distance value obtained from Google Maps. Genetic algorithms able to provide a solution that is close to the manual estimation using Google Maps. These results show the potential of genetic algorithms in improving the efficiency of delivery in the urban environment of Palembang City

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Availability

Inventory Code	Barcode	Call Number	Location	Status
2407003173	T145130	T1451302024	Central Library (REFERENCES)	Available but not for loan - Not for Loan

Detail Information

Series Title

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Call Number

T1451302024

Publisher

Indralaya : Prodi Teknik Informatika, Fakultas Ilmu Komputer Universitas Sriwijaya., 2024

Collation

xvi, VI-2 hlm.; ilus.; tab.; 29 cm.

Language

Indonesia

ISBN/ISSN

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Classification

518.107

Content Type

Text

Media Type

unmediated

Carrier Type

unspecified

Edition

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Subject(s)

Algoritma genetika
Prodi Teknik Informatika

Specific Detail Info

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Statement of Responsibility

UIN Farrah

Other version/related

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