Penyelesaian Asymmetric Clustered Travelling Salesman Problem dengan Simulated Annealing Hybrid pada Kasus Optimasi Rute Kunjungan Sales Hair-Care Product Yogyakarta

Destiano, Alif (2025) Penyelesaian Asymmetric Clustered Travelling Salesman Problem dengan Simulated Annealing Hybrid pada Kasus Optimasi Rute Kunjungan Sales Hair-Care Product Yogyakarta. Other thesis, Institut Teknologi Sepuluh Nopember.

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Abstract

Provinsi D.I. Yogyakarta, dengan banyaknya jalan satu arah, memiliki karakteristik yang sesuai dengan Asymmetric Travelling Salesman Problem (ATSP), di mana biaya atau jarak antar titik dapat memiliki nilai berbeda untuk perjalanan pergi dan kembali. Untuk meningkatkan efisiensi dan mengurangi biaya yang terkait dengan jaringan distribusi penjualan, diusulkan solusi untuk Asymmetric Clustered Travelling Salesman Problem (ACTSP) menggunakan algoritma Hybrid Simulated Annealing (HSA). ACTSP merupakan variasi dari Travelling Salesman Problem di mana titik lokasi berada pada klaster yang harus dikunjungi secara berurutan dan jarak antar titik berbeda ketika perjalanan pergi dan kembali. HSA merupakan penggabungan antara pendekatan pencarian global Simulated Annealing dengan perbaikan lokal menggunakan Iterated Local Search (ILS), yang bertujuan untuk mencapai solusi lebih optimal dan stabil dalam waktu komputasi yang efisien. Penelitian ini bertujuan untuk meminimalkan total panjang rute penjualan hair-care product oleh sales di Provinsi D.I. Yogyakarta. Data yang digunakan mencakup data dari TSPLIB dan data lokasi salon-salon yang dikunjungi yang diperoleh dari pihak Makarizo Professional. Berdasarkan hasil eksperimen, HSA mampu mengurangi jarak tempuh hingga 47,57% dari kondisi awal, serta menunjukkan performa yang lebih stabil dan presisi dibandingkan Simulated Annealing sederhana dan Hybrid Genetic Algorithm (HGA). Hasil ini menunjukkan bahwa HSA dapat diandalkan sebagai pendekatan optimasi rute pada kasus distribusi spasial seperti kunjungan lapangan sales.
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The Special Region of Yogyakarta, characterized by many one-way streets, aligns with the nature of the Asymmetric Travelling Salesman Problem (ATSP), where the cost or distance between points can differ depending on the direction of travel. To improve efficiency and reduce costs related to the sales distribution network, this study proposes a solution to the Asymmetric Clustered Travelling Salesman Problem (ACTSP) using the Hybrid Simulated Annealing (HSA) algorithm. ACTSP is a variant of the Travelling Salesman Problem where the locations are grouped into clusters that must be visited sequentially, and the distance between points is asymmetric. HSA combines the global search strategy of Simulated Annealing with local refinement via Iterated Local Search (ILS), aiming to achieve more optimal and stable solutions with efficient computational time. This research aims to minimize the total travel distance of hair-care product sales visits in the Yogyakarta area. The data used include benchmark datasets from TSPLIB and real-world salon location data provided by Makarizo Professional. Based on the experimental results, HSA was able to reduce the total travel distance by up to 47.57% from the initial condition and demonstrated more stable and accurate performance compared to basic Simulated Annealing and the Hybrid Genetic Algorithm (HGA). These findings indicate that HSA is a reliable approach for route optimization in spatial distribution problems such as sales field visits.

Item Type:	Thesis (Other)
Uncontrolled Keywords:	Simulated Annealing, Asymmetric Clustered Travelling Salesman Problem, Optimasi Rantai Pasok, Local Search, Supply Chain Optimization.
Subjects:	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:	Alif Destiano
Date Deposited:	22 Jul 2025 01:32
Last Modified:	22 Jul 2025 01:32
URI:	http://repository.its.ac.id/id/eprint/120361

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