Penyelesaian Kombinasi Vehicle Routing Problem Dan Container Loading Problem Menggunakan Algoritma Genetika

Prasetyaningrum, Ira (2007) Penyelesaian Kombinasi Vehicle Routing Problem Dan Container Loading Problem Menggunakan Algoritma Genetika. Masters thesis, Institut Teknologi Sepuluh November.

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Abstract

Kombinasi Vehicle Routing Problem dan Container Loading Problem (VRPCL) merupakan pengembangan model VRP yang juga memperhatikan proses optimisasi tata letak barang yang dimuat dalam kendaraan berdasarkan urutan kunjungan kendaraan serta memaksimumkan kegunaan ruang yang dimuat. Perusahaan menginginkan apabila dalam proses bongkar (unloading) di suatu customer tidak memerlukan proses pemindahan pallet untuk customer berikutnya sehingga dapat mempercepat proses serta mengurangi risiko kerusakan. Mengingat Vehicle Routing Problem dan Container Loading Problem keduanya merupakan problem berklasifikasi NP-hard problem, maka VRPCL juga akan berklasifikasi NP-hard problem. Penelitian ini membahas pengembangan model Vehicle Routing Problem combined with Container Loading Problem dan pengimplementasian algoritma genetika agar diperoleh jumlah kendaraan dan rute kendaraan dengan sisa ruang dalam kontainer yang minimum serta total jarak tempuh kontainer yang minimum. Operator genetika (seleksi, crossover, mutasi, dan regenerasi) akan diaplikasikan untuk menghasilkan populasi sehingga diperoleh kromosom baru dengan nilai fitness yang lebih baik. Kromosom pada populasi merepresentasikan nomor urutan masuk barang ke dalam kontainer. Pada penelitian ini juga dikembangkan model rancang bangun perangkat lunak (software prototype) untuk menyelesaikan VRPCL tersebut. Hasil yang didapat diharapkan dapat memberi masukan dalam pengambilan keputusan untuk menentukan urutan rute terpendek dari aktivitas distribusi dan jumlah kontainer yang dibutuhkan, serta dapat memberi alternatif metode dalam menyelesaikan VRPCL.
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Combination of Vehicle Routing Problem and Container Loading Problem (VRPCL) is a development of the VRP model that considers the optimization of the layout of objects loaded inside vehicles based on the vehicle visiting sequence, while also maximizing the utilization of the available loading space. The company aims to eliminate the need to move pallets for the next customer during the unloading process at a customer, so that the process can be completed faster and the risk of damage can be reduced. Considering that both Vehicle Routing Problem and Container Loading Problem are classified as NP-hard problems, VRPCL is also classified as an NP-hard problem. This research discusses the development of a Vehicle Routing Problem model combined with the Container Loading Problem and the implementation of a genetic algorithm to determine the number of vehicles and vehicle routes with minimum remaining space in containers and minimum total container travel distance. Genetic operators (selection, crossover, mutation, and regeneration) are applied to generate populations and obtain new chromosomes with better fitness values. The chromosomes in the population represent the loading sequence of goods into the containers. This research also develops a software prototype to solve the VRPCL problem. The results are expected to provide input for decision-making in determining the shortest route sequence for distribution activities and the number of containers required, as well as to provide an alternative method for solving VRPCL.

Item Type:	Thesis (Masters)
Additional Information:	RTI 658.5 Pra p
Uncontrolled Keywords:	Veh;c1e Rour;ng Problem, Conra;ner Load;ng Problem, Algoritma Genetika, Pallet, Perangkat Lunak, Vehicle Routing Problem, Container Loading Problem, Genetic Algoritluns, Software Prototype, Pallet.
Subjects:	H Social Sciences > HD Industries. Land use. Labor > HD38.5 Business logistics--Cost effectiveness. Supply chain management. ERP
Divisions:	Faculty of Industrial Technology > Industrial Engineering > 26101-(S2) Master Thesis
Depositing User:	magang .
Date Deposited:	28 Sep 2026 08:09
Last Modified:	28 Sep 2026 08:09
URI:	http://repository.its.ac.id/id/eprint/144984

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