Ibrahim, Erawan Faqih (2025) Penyelesaian Asymmetric Clustered Travelling Salesman Problem dengan Hybrid Genetic Algorithm pada Kasus Optimasi Rute Kunjungan Sales Hair-Care Product di Yogyakarta. Other thesis, Institut Teknologi Sepuluh Nopember.
![[thumbnail of 5026211001_Undergraduate_Thesis_Erawan Faqih Ibrahim.pdf]](http://repository.its.ac.id/style/images/fileicons/text.png) |
Text
5026211001_Undergraduate_Thesis_Erawan Faqih Ibrahim.pdf - Accepted Version Restricted to Repository staff only until 1 April 2027. Download (4MB) | Request a copy |
Abstract
Provinsi D.I. Yogyakarta, dengan karakteristik jalan satu arah, memiliki sifat yang sesuai dengan masalah Asymmetric Travelling Salesman Problem (ATSP), di mana jarak atau biaya antar lokasi dapat berbeda untuk perjalanan pergi dan kembali. Penelitian ini mengusulkan solusi untuk Asymmetric Clustered Travelling Salesman Problem (ACTSP) menggunakan Hybrid Genetic Algorithm (HGA), yang menggabungkan Genetic Algorithm (GA) dengan metode 3-opt local search untuk meningkatkan solusi dan menghindari jebakan optimum lokal. Pembagian lokasi salon dilakukan menggunakan Lloyd Clustering, yang bertujuan meminimalkan jarak antara titik data dan pusat klasternya (centroid) untuk menghasilkan pembagian wilayah yang lebih efisien. Penelitian ini bertujuan meminimalkan total jarak tempuh dalam rute distribusi penjualan hair-care product oleh sales di D.I. Yogyakarta. Berdasarkan hasil penelitian, total jarak tempuh yang semula 877.259 km pada rute asli berhasil dikurangi menjadi 764.043 km dengan HGA, dan lebih lanjut menjadi 459.9 km dengan kombinasi Lloyd Clustering dan HGA, mencerminkan peningkatan efisiensi sebesar 47.59%. Pendekatan ini terbukti meningkatkan efisiensi operasional secara signifikan dan dapat diadaptasi untuk aplikasi logistik lainnya.
==================================================================================================================================
The Special Region of Yogyakarta, with its characteristic one-way streets, aligns with the Asymmetric Travelling Salesman Problem (ATSP), where the distance or cost between locations can differ depending on the direction of travel. This study proposes a solution to the Asymmetric Clustered Travelling Salesman Problem (ACTSP) using a Hybrid Genetic Algorithm (HGA), which integrates the Genetic Algorithm (GA) with a 3-opt local search method to improve solutions and avoid local optima. The clustering of salon locations was performed using Lloyd Clustering, an iterative algorithm that minimizes the distance between data points and their cluster centroids to create more efficient regional divisions. This study aims to minimize the total travel distance for hair-care product sales representatives in the Special Region of Yogyakarta. Based on the results, the original travel distance of 1268.499 km was reduced to 764.043 km using HGA and further minimized to 459.9 km with the combination of Lloyd Clustering and HGA, representing a total efficiency improvement of 63.73%. This approach has proven to significantly enhance operational efficiency and holds potential for adaptation in other logistics applications.
| Item Type: | Thesis (Other) |
|---|---|
| Uncontrolled Keywords: | Optimasi Rantai Pasok, Asymmetric Clustered Travelling Salesman Problem, Hybrid Genetic Algorithm, Genetic Algorithm, Local Search, Lloyd Clustering, Supply Chain Optimization, Travelling Salesman Problem |
| Subjects: | T Technology > T Technology (General) > T57.6 Operations research--Mathematics. Goal programming T Technology > T Technology (General) > T57.84 Heuristic algorithms. |
| Divisions: | Faculty of Intelligent Electrical and Informatics Technology (ELECTICS) > Information System > 57201-(S1) Undergraduate Thesis |
| Depositing User: | Erawan Faqih Ibrahin |
| Date Deposited: | 22 Jan 2025 02:03 |
| Last Modified: | 22 Jan 2025 02:03 |
| URI: | http://repository.its.ac.id/id/eprint/116485 |
Actions (login required)
 |
View Item |