PENYELESAIAN CUTTING STOCK PROBLEM DUA DIMENSI MENGGUNAKAN ALGORITMA GREEDY RANDOMIZED ADAPTIVE SEARCH PROCEDURE, MERSENNE TWISTER DAN MODEL DOTTED BOARD

    Naja Rahma Maghriba, - and Kartika Yulianti, - and Al Azhary Masta, - (2025) PENYELESAIAN CUTTING STOCK PROBLEM DUA DIMENSI MENGGUNAKAN ALGORITMA GREEDY RANDOMIZED ADAPTIVE SEARCH PROCEDURE, MERSENNE TWISTER DAN MODEL DOTTED BOARD. S1 thesis, Universitas Pendidikan Indonesia.

    Abstract

    Cutting Stock Problem (CSP) dua dimensi adalah permasalahan optimasi dalam proses pemotongan bahan baku berbentuk lembaran datar (seperti papan, plat logam, atau kain) menjadi beberapa potongan berukuran lebih kecil untuk memenuhi permintaan tertentu, dengan tujuan utama meminimalkan sisa bahan atau memaksimalkan pemanfaatan area bahan. Penelitian ini menyelesaikan CSP dua dimensi menggunakan algoritma Greedy Randomized Adaptive Search Procedure (GRASP) dengan solusi awal dari bilangan acak Mersenne Twister (MT) dan diformulasikan ke dalam model Dotted Board. Algoritma GRASP menentukan pola pemotongan layak secara heuristik, sedangkan model Dotted Board untuk memformulasikan posisi peletakan masing-masing item dalam stock sehingga pola pemotongan dapat dihasilkan dan meminimalkan sisa bahan. Hasil penelitian CSP dengan data dari seorang ahli pemasangan plafon dengan bahan baku gypsum menunjukkan pola pemotongan yang menghasilkan susunan peletakan item dalam stock secara optimal, memenuhi seluruh permintaan serta meminimalkan sisa bahan. Berdasarkan hasil perhitungan, diperoleh tiga pola pemotongan optimal yang masing-masing digunakan sebanyak 7 kali, 6 kali, dan 17 kali untuk memenuhi seluruh kebutuhan. Program penyelesaian yang diimplementasikan menggunakan GUI Python dan LINGO berhasil memberikan solusi optimal dengan meminimalkan jumlah sisa bahan dan jumlah stock lembar yang diperlukan. The two-dimensional Cutting Stock Problem (CSP) is an optimization problem in the process of cutting raw material sheets (such as boards, metal plates, or fabric) into several smaller pieces to meet specific demands, with the main objective of minimizing leftover material or maximizing material utilization. This study addresses the two-dimensional CSP using the Greedy Randomized Adaptive Search Procedure (GRASP) algorithm, with an initial solution generated from Mersenne Twister (MT) random numbers and formulated into a Dotted Board model. The GRASP algorithm heuristically determines feasible cutting patterns, while the Dotted Board model formulates the placement positions of each item within the stock so that cutting patterns can be generated and material waste minimized. The results of this CSP study, using data from a ceiling installation specialist with gypsum as the raw material, produced cutting patterns that optimally arranged the item placements within the stock, fulfilling all demands while minimizing leftover material. Based on the calculation results, three optimal cutting patterns were obtained, used respectively 7 times, 6 times, and 17 times to meet the total requirements. The solution program, implemented using a Python-based GUI and LINGO, successfully provided optimal solutions by minimizing both leftover material and the number of raw stock sheets needed.

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    Official URL: https://repository.upi.edu/
    Item Type: Thesis (S1)
    Additional Information: ID SINTA Dosen Pembimbing: Kartika Yulianti: 5979108 Al Azhary Masta: 6007709
    Uncontrolled Keywords: Cutting Stock Problem, GRASP, Mersenne Twister, Dotted Board, Optimasi Cutting Stock Problem, GRASP, Mersenne Twister, Dotted Board, Optimization
    Subjects: L Education > L Education (General)
    Q Science > QA Mathematics
    Divisions: Fakultas Pendidikan Matematika dan Ilmu Pengetahuan Alam > Program Studi Matematika - S1 > Program Studi Matematika (non kependidikan)
    Depositing User: Naja Rahma Maghriba
    Date Deposited: 07 Aug 2025 01:53
    Last Modified: 07 Aug 2025 01:53
    URI: http://repository.upi.edu/id/eprint/134731

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