Multiple-choice knapsack-based heuristic algorithm for the two-stage two-dimensional cutting stock problem in the paper industry

2014 ◽  
Vol 52 (19) ◽  
pp. 5675-5689 ◽  
Author(s):  
Kyungdoc Kim ◽  
Byung-In Kim ◽  
Hyunbo Cho
Keyword(s):  
Heuristic Algorithm ◽  
Paper Industry ◽  
Multiple Choice ◽  
Cutting Stock Problem ◽  
Cutting Stock ◽  
Two Dimensional ◽  
Two Stage

Applying an Enhanced Heuristic Algorithm to a Constrained Two-Dimensional Cutting Stock Problem

2015 ◽  
Vol 9 (1L) ◽  
pp. 179-187
Author(s):  
Tzu-Yi Yu ◽  
Jiann-Cherng Yang ◽  
Yeong-Lin Lai ◽  
Chih-Cheng Chen ◽  
Han-Yu Chang
Keyword(s):  
Heuristic Algorithm ◽  
Cutting Stock Problem ◽  
Cutting Stock ◽  
Two Dimensional

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

A Hybrid Genetic Algorithm for Optimization of Two-Dimensional Cutting-Stock Problem

2012 ◽  
pp. 56-71
Author(s):  
Ahmed Mellouli ◽  
Faouzi Masmoudi ◽  
Imed Kacem ◽  
Mohamed Haddar
Keyword(s):  
Genetic Algorithm ◽  
Linear Programming ◽  
Production Cost ◽  
Programming Model ◽  
Hybrid Genetic Algorithm ◽  
Cutting Stock Problem ◽  
Cutting Stock ◽  
Two Dimensional ◽  
Genetic Approach ◽  
Cutting Pattern

In this paper, the authors present a hybrid genetic approach for the two-dimensional rectangular guillotine oriented cutting-stock problem. In this method, the genetic algorithm is used to select a set of cutting patterns while the linear programming model permits one to create the lengths to produce with each cutting pattern to fulfill the customer orders with minimal production cost. The effectiveness of the hybrid genetic approach has been evaluated through a set of instances which are both randomly generated and collected from the literature.

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