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All Journal Science and Technology Indonesia
Putra Bahtera Jaya Bangun
Jurusan matematika, Universitas Sriwijaya Sumatera Selatan, Indonesia
Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Environmental Science Materials Science & Nanotechnology Physics

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3-Phase Matheuristic Model in Two-Dimensional Cutting Stock Problem of Triangular Shape Items Putra Bahtera Jaya Bangun; Sisca Octarina; Sisca Puspita Sepriliani; Laila Hanum; Endro Sastro cahyono
Science and Technology Indonesia Vol. 5 No. 1 (2020): January
Publisher : Research Center of Inorganic Materials and Coordination Complexes, FMIPA Universitas Sriwijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1397.786 KB) | DOI: 10.26554/sti.2020.5.1.23-27

Abstract

Cutting Stock Problem (CSP) is a problem of cutting stocks with certain cutting rules. This study used the data of rectangular stocks, which cut into triangular shape items with various order sizes. The Modified Branch and Bound Algorithm (MBBA) was used to determine the optimum cutting pattern then formulated it into the 3-Phase Matheuristic model which consisted of constructive phase, improvement phase, and compaction phase. Based on the results, it showed that the MBBA produces three optimum cutting patterns, which was used six times, eight times, and four times respectively to fulfill the consumer demand. Then the cutting patterns were formulated into the 3-Phase Matheuristic model whereas the optimum solution was the minimum trim loss for the first, second and third patterns.
Set Covering Model in Solving Multiple Cutting Stock Problem Sisca Octarina; Devi Gusmalia Juita; Ning Eliyati; Putra Bahtera Jaya Bangun
Science and Technology Indonesia Vol. 5 No. 4 (2020): October
Publisher : Research Center of Inorganic Materials and Coordination Complexes, FMIPA Universitas Sriwijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (943.33 KB) | DOI: 10.26554/sti.2020.5.4.121-130

Abstract

Cutting Stock Problem (CSP) is the determination of how to cut stocks into items with certain cutting rules. A diverse set of stocks is called multiple stock CSP. This study used Pattern Generation (PG) algorithm to determine cutting pattern, then formulated it into a Gilmore and Gomory model and solved by using Column Generation Technique (CGT). Set Covering model was generated from Gilmore and Gomory model. Based on the results, selected cutting patterns in the first stage can be used in the second stage. The combination of patterns generated from Gilmore and Gomory model showed that the use of stocks was more effective than Set Covering model.
Column Generation Model in Capacitated Multi-Periods Cutting Stock Problem with Pattern Set-Up Cost Putra Bahtera Jaya Bangun; Sisca Octarina; Laila Hanum; Ranti Sawitri; Endro Sastro Cahyono
Science and Technology Indonesia Vol. 6 No. 1 (2021): January
Publisher : Research Center of Inorganic Materials and Coordination Complexes, FMIPA Universitas Sriwijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1195.562 KB) | DOI: 10.26554/sti.2021.6.1.8-13

Abstract

Cutting Stock Problem (CSP) determines the cutting of stocks with standard length and width to meet the item’s demand. The optimal cutting pattern will minimize the usage of stocks and trim loss. This research implemented the pattern generation algorithm to form the Gilmore-Gomory and Column Generation model in two-dimensional CSP. The CSP in this research had three periods of cutting with different capacities in each period. The Column Generation model added the pattern set-up cost as the constraint. The Gilmore-Gomory model ensured that the first stage’s strips were used in the second stage and met the item’s demand. Based on the Column Generation model’s solution, the 1st period used the 2nd, 4th, and 5th patterns, the 2nd period used 4th and 5th patterns, and the 3rd period did not use any patterns. The first and second periods fulfilled all of the demands.
Co-Authors Devi Gusmalia Juita Endro Sastro cahyono Laila Hanum Ning Eliyati Ranti Sawitri Sisca Octarina Sisca Puspita Sepriliani