VND in CVRP, MDVRP, and VRPTW cases

Satyananda, Darmawan; Wahyuningsih, Sapti

doi:10.1088/1742-6596/1320/1/012025

Cited by 5 publications

(3 citation statements)

References 17 publications

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“…Penelitian terdahulu tentang varian VRP. Penelitian terdahulu tentang varian VRP dapat dilihat pada (Afshar-Nadjafi & Afshar-Nadjafi, 2017), (Yang, 2021), (Kyriakakis, 2021), (Satyananda & Wahyuningsih, 2019b), (Wahyuningsih & Satyananda, 2015), (Wahyuningsih & Satyananda, 2014), (Wahyuningsih & Satyananda, 2018), dan (Wahyuningsih & Satyananda, 2020. Salah satu varian dari VRP adalah Capacitated Vehicle Routing Problem with Time Windows (CVRPTW).…”

Section: Pendahuluanunclassified

Algoritma General Variable Neighborhood Search Pada Capacitated Vehicle Routing Problem With Time Windows Dan Implementasinya

Fadila¹,

Wahyuningsih²,

Satyananda³

2022

JKMA

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The Capacitated Vehicle Routing Problem with Time Windows (CVRPTW) is one of the variants of the Vehicle Routing Problem (VRP), which is the problem of determining the optimal route from the depot to the consumer which is located spread out with different requests. In CVRPTW problem solving considers capacity and time constraints. Determining the optimal route can reduce costs and energy spent during the distribution process. The General Variable Neighborhood Search (GVNS) algorithm can be applied to the CVRPTW problem. The GVNS algorithm is an improvement on the VNS algorithm using RVND. The GVNS algorithm starts with finding the initial solution, continues with perturbation, and then the repair procedure is carried out. Perturbation and improvements to the GVNS algorithm are performed repeatedly according to the predetermined IterMax. The GVNS algorithm for CVRPTW will be implemented using the Borland Delphi 7.0 programming language. The product in the form of this application can be used more practically to solve CVRPTW problems using the GVNS algorithm.

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Section: Pendahuluanunclassified

Algoritma General Variable Neighborhood Search Pada Capacitated Vehicle Routing Problem With Time Windows Dan Implementasinya

Fadila¹,

Wahyuningsih²,

Satyananda³

2022

JKMA

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“…Tujuan CVRP adalah untuk mencari rute pendistribusian yang optimal, yaitu rute yang memiliki total jarak tempuh minimal dan waktu paling efektif sehingga didapatkan biaya pendistribusian yang minimum. Sumber rujukan tentang CVRP dapat dilihat pada (Wahyuningsih & Satyananda, 2018), (Satyananda & Wahyuningsih, 2019), (Krebs & Ehmke, 2021), (Doan et al, 2021), dan (Ewert et al, 2021) Hasil penyelesaian masalah CVRP digambarkan dalam bentuk rute dari graph Penyelesian layak masalah CVRP merupakan himpunan rute dimana rute dikunjungi sejumlah kendaraan dari depot ke semua pelanggan tepat satu kali dengan permintaan yang sudah ditentukan serta tidak melanggar kendala kapasitas. Permasalahan CVRP telah banyak diselesaikan dengan menggunakan berbagai macam algoritma, baik algoritma heuristic maupun algoritma metaheuristic.…”

Section: Pendahuluanunclassified

Algoritma Gravitional Emulation Local Search Pada CVRP Dan Implementasinya

Azis

Wahyuningsih²,

Satyananda

2022

JKMA

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Permasalahan optimalisasi distribusi dapat dipecahkan dengan menggunakan algoritma pada varian Vehicle Routing Problem (VRP). Salah satu varian dari VRP adalah Capacitated Vehicle Routing Problem (CVRP) yaitu dengan tambahan kendala kapasitas kendaraan yang identik. Algoritma Gravitational Emulation Local Search (GELS) dapat digunakan untuk menentukan solusi CVRP. Algorima GELS merupakan gabungan dari algoritma genetika dan local search (best improvement local search). Pada artikel ini dibahas langkah algoritma dan diimplementasikan ke dalam computer menggunakan aplikasi Borland Delphi 7. Input program berupa ukuran populasi, probabilitas crossover, probabilitas mutasi, maksimum iterasi, kapasitas kendaraan, banyaknya titik, dan permintaan setiap customer. Output berupa hasil rute dengan jarak yang ditempuh serta divisualisasi rutenya dengan gambar graph. Diberikan contoh penyelesaian permasalahan dengan contoh 7 titik terdiri dari satu depot dan enam customer. Hasil tampilan program berupa matrik bobot titik, permintaan, dan hasil berupa rute optimal. Aplikasi program GELS pada CVRP secara praktis dapat digunakan untuk penyelesaian optimasi distribusi.

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“…Di sisi lain, proses berhenti jika semua neighborhood telah dieksplorasi dan tidak ada perbaikan ditemukan (Herrán et al, 2019). Beberapa penelitian yang menggunakan algoritma VND untuk menyelesaikan suatu permasalahan di antaranya Vehicle Routing Problem with Time Windows (Harzi andKrichen, 2017), Capacitated Vehicle Routing Problem (Amous et al, 2017), dan pada CVRP, MDVRP, dan VRPTW (Satyananda and Wahyuningsih, 2019).…”

Section: Pendahuluanunclassified

Algoritma Variable Neighborhood Descent (Vnd) Pada Vehicle Routing Problem With Simultaneous Delivery and Pickup (Vrpsdp) Dan Implementasinya

Christopher

Wahyuningsih

Satyananda

2021

JKMA

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Vehicle Routing Problem with Simultaneous Delivery and Pickup (VRPSDP) is a variant of Vehicle Routing Problem (VRP). VRPSDP has special constraints, namely requests and returns are carried out simultaneously. In this article we will use the Variable Neighborhood Descent (VND) algorithm to solve VRPSDP problems. There are two steps taken to use the VND algorithm on VRPSDP, namely finding an initial solution with the Insertion Heuristic algorithm and improving the position of the customer by using the neighborhood operator on the VND algorithm. The implementation of the VND algorithm on VRPSDP has been successfully made using the Borland Delphi 7.0 programming language. Inputs contained in the program are point position, distance between points, customer requests and returns and vehicle capacity. The output contained in the program in the form of routes that have been completed using an algorithm and output in the form of images of the final solution that has been obtained. Based on the results obtained, an example with 6 customers produces 3 routes with a total distance of 266 km, while an example with 10 customers produces 4 routes with a total distance of 100 km.

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VND in CVRP, MDVRP, and VRPTW cases

Cited by 5 publications

References 17 publications

Algoritma General Variable Neighborhood Search Pada Capacitated Vehicle Routing Problem With Time Windows Dan Implementasinya

Algoritma General Variable Neighborhood Search Pada Capacitated Vehicle Routing Problem With Time Windows Dan Implementasinya

Algoritma Gravitional Emulation Local Search Pada CVRP Dan Implementasinya

Algoritma Variable Neighborhood Descent (Vnd) Pada Vehicle Routing Problem With Simultaneous Delivery and Pickup (Vrpsdp) Dan Implementasinya

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