scholarly journals COLUMN GENERATION TECHNIQUE FOR SOLVING TWO-DIMENSIONAL CUTTING STOCK PROBLEMS: METHOD OF STRIPE APPROACH

2012 ◽  
Vol 13 (2) ◽  
Author(s):  
K. Novianingsih ◽  
R. Hadianti ◽  
S. Uttunggadewa
Keyword(s):  
Column Generation ◽  
Cutting Stock ◽  
Two Dimensional ◽  
Generation Technique

scholarly journals Set Covering Model in Solving Multiple Cutting Stock Problem

2020 ◽  
Vol 5 (4) ◽  
pp. 121
Author(s):  
Sisca Octarina ◽  
Devi Gusmalia Juita ◽  
Ning Eliyati ◽  
Putra Bahtera Jaya Bangun
Keyword(s):  
Column Generation ◽  
Pattern Generation ◽  
Cutting Stock Problem ◽  
Set Covering ◽  
Cutting Stock ◽  
Second Stage ◽  
Generation Technique ◽  
Cutting Pattern ◽  
Covering Model

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.  

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

The Nesting of Two-Dimensional Shapes Using Genetic Algorithms

1995 ◽  
Vol 209 (2) ◽  
pp. 115-124 ◽  
Author(s):  
H S Ismail ◽  
K K B Hon
Keyword(s):  
Genetic Algorithms ◽  
Evolutionary Process ◽  
Search Space ◽  
Cutting Stock ◽  
Two Dimensional ◽  
Optimal Solutions ◽  
Spatial Constraints ◽  
Global Optimal ◽  
Optimum Solution ◽  
Rapid Conversion

The general two-dimensional cutting stock problem is concerned with the optimum layout and arrangement of two-dimensional shapes within the spatial constraints imposed by the cutting stock. The main objective is to maximize the utilization of the cutting stock material. This paper presents some of the results obtained from applying a combination of genetic algorithms and heuristic approaches to the nesting of dissimilar shapes. Genetic algorithms are stochastically based optimization approaches which mimic nature's evolutionary process in finding global optimal solutions in a large search space. The paper discusses the method by which the problem is defined and represented for analysis and introduces a number of new problem-specific genetic algorithm operators that aid in the rapid conversion to an optimum solution.

An approach to two-dimensional cutting stock problems

1987 ◽  
Vol 25 (2) ◽  
pp. 175-190 ◽  
Author(s):  
CİHAN H. DAGLI ◽  
M. YALÇIN TATOGLU
Keyword(s):  
Cutting Stock ◽  
Two Dimensional
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