The N-Sheet Model in Capacitated Multi-Period Cutting Stock Problem with Pattern Set-Up Cost (similarity)

Octarina, Sisca and Zayanti, Des Alwine and Bangun, Putra Bahtera Jaya and PEBRINA, SISCA and Hanum, Laila The N-Sheet Model in Capacitated Multi-Period Cutting Stock Problem with Pattern Set-Up Cost (similarity). Turnitin Universitas Sriwijaya. (Submitted)

[thumbnail of The N-Sheet Model in Capacitated Multi-Period Cutting Stock Problem with Pattern Set-Up Cost.pdf]
Preview
Text
The N-Sheet Model in Capacitated Multi-Period Cutting Stock Problem with Pattern Set-Up Cost.pdf

Download (11MB) | Preview

Abstract

Cutting Stock Problem (CSP) is a problem to optimize the stock usage with specifics cutting patterns. This research implemented the N-Sheet model in Capacitated Multi- Period Cutting Stock Problem with the pattern set-up cost. This study used the data of the rectangular stocks, which cut to a variety of item sizes. The Pattern Generation (PG) algorithm determined the cutting patterns. The PG produced 21 optimal patterns based on the length and 23 optimal patterns based on the width to fulfil customer requirements. And then, we formulated the patterns into the N-Sheet model. The optimal solution from the N-Sheet model in this research were six cutting patterns. We used the 1st, 2nd, 5th, and 19th patterns for cutting based on length, and the 4th and 23rd patterns for cutting based on the width. The solutions of the model were not so optimal because it yielded too many surplus items.

Item Type: Other
Uncontrolled Keywords: Cutting Stock Problem, Pattern Generation, NSheet, Multi-Period, Pattern
Subjects: #3 Repository of Lecturer Academic Credit Systems (TPAK) > Results of Ithenticate Plagiarism and Similarity Checker
Divisions: 08-Faculty of Mathematics and Natural Science > 44201-Mathematics (S1)
Depositing User: Putra Bahtera Jaya Bangun
Date Deposited: 08 Sep 2022 00:27
Last Modified: 03 Jul 2024 01:42
URI: http://repository.unsri.ac.id/id/eprint/78076

Actions (login required)

View Item View Item