IMPLEMENTASI ALGORITMA GENETIKA PADA PENYELESAIAN MULTI-OBJECTIVE FUZZY CAPACITATED VEHICLE ROUTING PROBLEM WITH TIME WINDOWS

Nabila Berliani, - and Khusnul Novianingsih, - and Ririn Sispiyati, - (2025) IMPLEMENTASI ALGORITMA GENETIKA PADA PENYELESAIAN MULTI-OBJECTIVE FUZZY CAPACITATED VEHICLE ROUTING PROBLEM WITH TIME WINDOWS. S1 thesis, Universitas Pendidikan Indonesia.

Abstract

Permasalahan Vehicle Routing Problem with Time Windows (VRPTW) merupakan salah satu tantangan utama dalam distribusi logistik, khususnya ketika mempertimbangkan kapasitas kendaraan (Capacitated Vehicle Routing Problem), batasan waktu, serta ketidakpastian waktu mulai melayani pelanggan yang bersifat fuzzy. Penelitian ini mengusulkan pendekatan Algoritma Genetika, Bilangan Fuzzy Segitiga, dan Weighted Sum Model untuk menyelesaikan Multi-Objective Fuzzy Capacitated Vehicle Routing Problem with Time Windows (MOF-CVRPTW). Kemudian, akan diimplementasikan untuk penyelesaian masalah pendistribusian barang oleh distributor. Tujuan dari penelitian ini adalah meminimumkan total waktu distribusi, jumlah pelanggan yang terlewat, total biaya dalam melayani semua pelanggan, dan memaksimumkan tingkat kepuasan pelanggan. Hasil eksperimen menunjukkan bahwa algoritma genetika mampu menghasilkan solusi yang optimal dan layak diterapkan dalam skenario distribusi nyata. Kata Kunci: Multi-Objective Optimization, Fuzzy, Capacitated Vehicle Routing Problem with Time Windows, Algoritma Genetika, Bilangan Fuzzy Segitiga, Weighted Sum Model The Vehicle Routing Problem with Time Windows (VRPTW) is one of the main challenges in logistics distribution, especially when considering vehicle capacity (Capacitated Vehicle Routing Problem), time constraints, and the uncertainty of fuzzy customer service start times. This study proposes an approach combining Genetic Algorithms, Fuzzy Triangle Numbers, and the Weighted Sum Model to solve the Multi-Objective Fuzzy Capacitated Vehicle Routing Problem with Time Windows (MOF-CVRPTW). It will then be implemented to solve the problem of goods distribution by distributors. The objective of this study is to minimize total distribution time, the number of missed customers, total costs in serving all customers, and maximize customer satisfaction levels. Experimental results show that the genetic algorithm is capable of generating optimal solutions and is feasible for application in real-world distribution scenarios. Keywords: Multi-Objective Optimization, Fuzzy, Vehicle Routing Problem with Capacity and Time Window, Genetic Algorithm, Fuzzy Triangle Numbers, Weighted Sum Model

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Item Type:	Thesis (S1)
Additional Information:	ID SINTA Dosen Pembimbing: Khusnul Novianingsih: 258640 Ririn Sispiyati: 5986406
Uncontrolled Keywords:	Multi-Objective Optimization, Fuzzy, Capacitated Vehicle Routing Problem with Time Windows, Algoritma Genetika, Bilangan Fuzzy Segitiga, Weighted Sum Model Multi-Objective Optimization, Fuzzy, Vehicle Routing Problem with Capacity and Time Window, Genetic Algorithm, Fuzzy Triangle Numbers, Weighted Sum Model
Subjects:	L Education > L Education (General) Q Science > QA Mathematics
Divisions:	Fakultas Pendidikan Matematika dan Ilmu Pengetahuan Alam > Program Studi Matematika - S1
Depositing User:	Nabila Berliani
Date Deposited:	06 Sep 2025 09:31
Last Modified:	06 Sep 2025 09:31
URI:	http://repository.upi.edu/id/eprint/137671

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