PENYELESAIAN FUZZY CAPACITATED VEHICLE ROUTING PROBLEM DENGAN BILANGAN FUZZY TRAPESIUM DIPERUMUM MENGGUNAKAN ADAPTIVE GENETIC ALGORITHM

Adinda Shyfa Dianissa, - and Khusnul Novianingsih, - and Sumanang Muhtar Gozali, - (2025) PENYELESAIAN FUZZY CAPACITATED VEHICLE ROUTING PROBLEM DENGAN BILANGAN FUZZY TRAPESIUM DIPERUMUM MENGGUNAKAN ADAPTIVE GENETIC ALGORITHM. S1 thesis, Universitas Pendidikan Indonesia.

Abstract

Penelitian ini membahas Capacitated Vehicle Routing Problem (CVRP) yang merupakan salah satu permasalahan optimasi klasik dalam distribusi logistik, di mana sejumlah kendaraan dengan kapasitas terbatas harus mengunjungi sejumlah konsumen dengan permintaan tertentu secara efisien. Waktu tempuh antar lokasi diasumsikan tidak pasti sebagai bilangan fuzzy trapesium diperumum. Untuk menyelesaikan model tersebut, digunakan pendekatan Adaptive Genetic Algorithm (AGA) yang merupakan pengembangan dari Genetic Algorithm yang dapat menyesuaikan laju crossover dan mutasi secara dinamis selama proses evolusi. Pendekatan AGA ini menjadi salah satu pembeda utama dari penelitian-penelitian sebelumnya. Penelitian ini mengimplementasikan model Fuzzy Capacitated Vehicle Routing Problem (FCVRP) pada kasus distribusi gas LPG oleh salah satu agen di Kabupaten Karawang. Hasil simulasi menunjukkan bahwa pendekatan ini mampu meminimalkan total waktu tempuh distribusi. Pada skenario optimal, waktu tempuh minimum yang diperoleh adalah 113,64 menit dengan kombinasi parameter terbaik yaitu ukuran populasi sebesar 100, nilai maksimum crossover 0,9, nilai minimum mutasi 0,1, dan generasi sebanyak 50.

This study discusses the Capacitated Vehicle Routing Problem (CVRP), which is one of the classic optimization problems in logistics distribution, where a number of vehicles with limited capacity must efficiently visit a set of customers with specific demands. The travel time between locations is assumed to be uncertain and represented as a generalized trapezoidal fuzzy number. To solve this model, an Adaptive Genetic Algorithm (AGA) is used, which is an enhancement of the traditional Genetic Algorithm that dynamically adjusts the crossover and mutation rates during the evolutionary process. The use of AGA serves as a key differentiator from previous studies, which typically rely on conventional genetic algorithms. This research implements the Fuzzy Capacitated Vehicle Routing Problem (FCVRP) model in the case of LPG gas distribution by an agent in Karawang Regency. The simulation results show that this approach is capable of minimizing the total travel time for distribution. In the optimal scenario, the minimum travel time obtained is 113.64 minutes, with the best parameter combination being a population size of 100, a maximum crossover rate of 0.9, a minimum mutation rate of 0.1, and 50 generations.

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Official URL: https://repository.upi.edu/
Item Type: Thesis (S1)
Additional Information: https://scholar.google.com/citations?view_op=new_profile&hl=en ID SINTA Dosen Pembimbing: Khusnul Novianingsih: 258640 Sumanang Muhtar Gozali: 6121808
Uncontrolled Keywords: Fuzzy Capacitated Vehicle Routing Problem, Fuzzy Trapesium Diperumum, Adaptive Genetic Algorithm, Optimisasi Rute, Distribusi Gas LPG. Fuzzy Capacitated Vehicle Routing Problem, Generalized Trapezoidal Fuzzy Numbers, Adaptive Genetic Algorithm, Route Optimization, LPG Distribution.
Subjects: Q Science > QA Mathematics
Divisions: Fakultas Pendidikan Matematika dan Ilmu Pengetahuan Alam > Program Studi Matematika - S1 > Program Studi Matematika (non kependidikan)
Depositing User: Adinda Shyfa Dianissa
Date Deposited: 06 May 2025 07:38
Last Modified: 06 May 2025 07:38
URI: http://repository.upi.edu/id/eprint/132989

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