Comparative analysis of pattern-based models for the two-dimensional two-stage guillotine cutting stock problem

2019 ◽  
Vol 109 ◽  
pp. 159-169
Author(s):  
Sue-Jeong Kwon ◽  
Seulgi Joung ◽  
Kyungsik Lee
Keyword(s):  
Comparative Analysis ◽  
Cutting Stock Problem ◽  
Cutting Stock ◽  
Two Dimensional ◽  
Two Stage ◽  
Guillotine Cutting

A column generation heuristic for the two-dimensional two-staged guillotine cutting stock problem with multiple stock size

2012 ◽  
Vol 218 (1) ◽  
pp. 251-260 ◽  
Author(s):  
Fabio Furini ◽  
Enrico Malaguti ◽  
Rosa Medina Durán ◽  
Alfredo Persiani ◽  
Paolo Toth
Keyword(s):  
Column Generation ◽  
Cutting Stock Problem ◽  
Cutting Stock ◽  
Two Dimensional ◽  
Stock Size ◽  
Guillotine Cutting

GRASP and Path Relinking for the Two-Dimensional Two-Stage Cutting-Stock Problem

2007 ◽  
Vol 19 (2) ◽  
pp. 261-272 ◽  
Author(s):  
Ramón Alvarez-Valdes ◽  
Rafael Martí ◽  
Jose M. Tamarit ◽  
Antonio Parajón
Keyword(s):  
Cutting Stock Problem ◽  
Path Relinking ◽  
Cutting Stock ◽  
Two Dimensional ◽  
Two Stage

scholarly journals Linear Integer Optimization Model for Two-Stage Guillotine Cutting Stock Problem Using Branch and Bound Method in the Garment Industry

2020 ◽  
Vol 1 (1) ◽  
pp. 40-52
Author(s):  
Eman Lesmana ◽  
Julita Nahar ◽  
Annisa D. P
Keyword(s):  
Branch And Bound ◽  
Optimal Solution ◽  
Garment Industry ◽  
Cutting Stock Problem ◽  
Cutting Stock ◽  
Branch And Bound Method ◽  
Integer Optimization ◽  
Two Stage ◽  
Stock Cutting ◽  
Guillotine Cutting

This paper discusses the Two-Stage Guillotine Cutting Stock Problem (2GCSP) in the garment industry, namely how to determine the two-stage guillotine pattern that is used to cut fabric stocks into several certain size t-shirt materials that are produced based on the demand for each size of the shirt. 2GCSP is modeled in the form of Linear Integer Optimization and finding solutions using the Branch and Bound method. In this paper also presented a Graphical User Interface with Maple software as an interactive tool to find the best fabric stock cutting patterns. The results show that the optimal solution can be determined by solving numerically using the Branch and Bound method and Maple optimization packages. The solution is shown with an illustration of the pattern and the amount of fabric cut based on the pattern.

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