PENYELESAIAN PENENTUAN JALUR EVAKUASI OPTIMAL DENGAN ALGORITMA GENETIKA ADAPTIF (STUDI KASUS DI KAMPUNG PENCUT LEMBANG)

Fairuz Cahyohartoto, - (2019) PENYELESAIAN PENENTUAN JALUR EVAKUASI OPTIMAL DENGAN ALGORITMA GENETIKA ADAPTIF (STUDI KASUS DI KAMPUNG PENCUT LEMBANG). S1 thesis, Universitas Pendidikan Indonesia.

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Official URL: http://repository.upi.edu

Abstract

Patahan Lembang merupakan zona rawan gempa dimana hal ini menjadi sebuah ancaman bagi penduduk yang tinggal tepat di atas patahan Lembang, salah satunya adalah Kampung Pencut. Oleh karena itu, dibutuhkan jalur evakuasi di Kampung Pencut untuk mengantisipasi apabila terjadi gempa yang disebabkan oleh Patahan Lembang. Tempat evakuasi akhir yang berada di Kampung Pencut lebih dari satu sehingga model yang digunakan adalah model Multi-Depot Vehicle Routing Problem (MDVRP). Algoritma genetika adaptif dapat digunakan untuk memperoleh jalur evakuasi optimal terutama pada kasus MDVRP. Penggunaan algoritma genetika adaptif bertujuan untuk menghindari kondisi dimana terjebak pada optimum lokal. Cara kerja algoritma genetika adaptif yaitu representasi kromosom, pembangkitan populasi, seleksi, crossover dan mutasi. Perbedaan antara algoritma genetika adaptif dengan algoritma genetika standar terletak pada probabilitas crossover dan probabilitas mutasi. Dalam penelitian ini, algoritma genetika adaptif diimplementasikan pada penyelesaian penentuan jalur evakuasi di Kampung Pencut. Berdasarkan hasil implementasi dapat disimpulkan bahwa algoritma genetika adaptif mampu memberikan solusi jalur evakuasi optimal di Kampung Pencut.;---Lembang Fault is an earthquake-prone zone where it becomes a threat to residents who live just above the Lembang fault, one of which is Pencut Village. Therefore, an evacuation route is needed in Kamput Pencut to anticipate an earthquake caused by the Lembang Fault. The final evacuation site in Kamput Pencut is more than one, so the model used is the Multi-Depot Vehicle Routing Problem (MDVRP) model. Adaptive genetic algorithms can be used to obtain optimal evacuation paths, especially in MDVRP cases. The use of adaptive genetic algorithms aims to avoid conditions where it is trapped at a local optimum. The workings of adaptive genetic algorithms are chromosome representation, population generation, selection, crossover and mutation. The difference between adaptive genetic algorithms and standard genetic algorithms lies in crossover probabilities and mutation probabilities. In this study, an adaptive genetic algorithm was implemented in the completion of the evacuation route in Kamput Pencut. Based on the results of the implementation it can be concluded that the adaptive genetic algorithm is able to provide optimal evacuation path solutions in Pencut Village.

Item Type: Tugas Akhir,Skripsi,Tesis,Disertasi (S1)
Additional Information: No. Panggil :S_MAT_FAI p-2019; Nama Pembimbing : I.Dr.Khusnul Novianingsih, II.Dra.Hj.Rini Marwati; NIM :1405755;
Uncontrolled Keywords: Genetic algorithms. Adaptive genetic algorithms. Multi-Depot Vehicle Routing Problem. Evacuation Paths Determination. Minimum Distance.;---Algoritma Genetika, Algoritma Genetika Adaptif. Multi-Depot Vehicle Routing Problem. Penentuan Jalur Evakuasi. Jarak Minimum.
Subjects: L Education > L Education (General)
Q Science > QA Mathematics
Divisions: Fakultas Pendidikan Matematika dan Ilmu Pengetahuan Alam > Jurusan Pendidikan Matematika
Depositing User: Ryan Taufiq Qurrohman
Date Deposited: 11 Mar 2020 09:03
Last Modified: 11 Mar 2020 09:03
URI: http://repository.upi.edu/id/eprint/47823

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