Penyelesaian Asymmetric Clustered Travelling Salesman Problem dengan Ant Colony Optimization pada Kasus Kontrol SPBU di Surabaya

Aditya, Farrel Istihsan (2024) Penyelesaian Asymmetric Clustered Travelling Salesman Problem dengan Ant Colony Optimization pada Kasus Kontrol SPBU di Surabaya. Other thesis, Institut Teknologi Sepuluh Nopember.

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Abstract

Dalam manajemen rantai pasok, aktivitas distribusi harus dikelola dengan efektif. Biaya pada proses distribusi berpengaruh terhadap harga jual akhir sebuah produk. Oleh karena itu, perusahaan perlu mempertimbangkan biaya untuk distribusi. Masalah tersebut dapat diselesaikan dengan mengoptimalkan jalur distribusi yang telah ada sehingga dapat mengurangi biaya yang dikeluarkan selama distribusi. Masalah optimasi rute ini dikenal dengan Travelling Salesman Problem (TSP). Dalam implementasinya di dunia nyata, banyak variasi yang berkembang untuk TSP, salah satunya adalah Asymmetric Clustered Travelling Salesman Problem (ACTSP). ACTSP merupakan variasi TSP dengan kota-kota yang ada berada pada beberapa klaster dan setiap kota pada klaster harus dikunjungi secara berurutan. Biaya pulang dan pergi antar kota pada ACTSP akan berbeda. Pada penelitian ini, ACTSP akan diselesaikan dengan algoritma Ant Colony Optimization (ACO). ACO adalah metode algoritma metaheuristik yang terinsipirasi dari cara alami semut saat mencari makan. Kemudian ACO akan diterapkan pada studi kasus penentuan rute petugas kontrol SPBU di Surabaya.
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In supply chain management, distribution activities must be managed effectively. Costs in the distribution process affect the final selling price of a product. Therefore, companies need to consider distribution costs. This problem can be solved by optimizing existing distribution channels so as to reduce costs incurred during distribution. This route optimization problem is known as the Traveling Salesman Problem (TSP). In its implementation in the real world, many variations have developed for TSP, one of which is the Asymmetric Clustered Traveling Salesman Problem (ACTSP). ACTSP is a variation of TSP with cities located in several clusters and each city in the cluster must be visited sequentially. The cost of going home and going
between cities on ACTSP will be different. In this research, ACTSP will be completed using the Ant Colony Optimization (ACO) algorithm. ACO is a metaheuristic algorithm method
inspired by the natural way ants search for food. Then ACO will be applied to a case study of determining routes for gas station control officers in Surabaya.

Item Type:	Thesis (Other)
Uncontrolled Keywords:	Ant Colony Optimization, Asymmetric Clustered Travelling Salesman Problem, Distribution, Opposition-Based Learning, Ant Colony Optimization, Asymmetric Clustered Travelling Salesman Problem, Distribusi, Opposition-Based Learning.
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:	Farrel Istihsan Aditya
Date Deposited:	25 Jul 2024 03:32
Last Modified:	25 Jul 2024 03:32
URI:	http://repository.its.ac.id/id/eprint/108860

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