A Local Search Approach for the Pattern Restricted One Dimensional Cutting Stock Problem

2003 ◽  
pp. 673-698
Author(s):  
Shunji Umetani ◽  
Mutsunori Yagiura ◽  
Toshihide Ibaraki
Keyword(s):  
Local Search ◽  
Cutting Stock Problem ◽  
Cutting Stock ◽  
One Dimensional ◽  
Search Approach

A Least-Loss Algorithm for a Bi-Objective One-Dimensional Cutting-Stock Problem

2019 ◽  
Vol 6 (2) ◽  
pp. 1-19 ◽  
Author(s):  
Hesham K. Alfares ◽  
Omar G. Alsawafy
Keyword(s):  
Real Life ◽  
Cutting Stock Problem ◽  
Cutting Stock ◽  
Benchmark Problems ◽  
Standard Size ◽  
One Dimensional ◽  
Small Item ◽  
Proposed Model ◽  
Trim Loss ◽  
Industrial Problem

This article presents a new model and an efficient solution algorithm for a bi-objective one-dimensional cutting-stock problem. In the cutting-stock—or trim-loss—problem, customer orders of different smaller item sizes are satisfied by cutting a number of larger standard-size objects. After cutting larger objects to satisfy orders for smaller items, the remaining parts are considered as useless or wasted material, which is called “trim-loss.” The two objectives of the proposed model, in the order of priority, are to minimize the total trim loss, and the number of partially cut large objects. To produce near-optimum solutions, a two-stage least-loss algorithm (LLA) is used to determine the combinations of small item sizes that minimize the trim loss quantity. Solving a real-life industrial problem as well as several benchmark problems from the literature, the algorithm demonstrated considerable effectiveness in terms of both objectives, in addition to high computational efficiency.

Application of the Two-Stage One-Dimensional Cutting Stock Problem in the Steel Industry

2018 ◽  
Author(s):  
Jose Luis Santos ◽  
Joni Santos ◽  
Manuel Joao Ferreira ◽  
Nelson Alves ◽  
Miguel Guevara
Keyword(s):  
Steel Industry ◽  
Cutting Stock Problem ◽  
Cutting Stock ◽  
Two Stage ◽  
One Dimensional

Heuristics for the integer one-dimensional cutting stock problem: A computational study

OR Spectrum ◽  
1996 ◽  
Vol 18 (3) ◽  
pp. 131-144 ◽  
Author(s):  
Gerhard W�scher ◽  
Thomas Gau
Keyword(s):  
Computational Study ◽  
Cutting Stock Problem ◽  
Cutting Stock ◽  
One Dimensional
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