Integrated lot-sizing and one-dimensional cutting stock problem with usable leftovers

2020 ◽  
Author(s):  
D. N. do Nascimento ◽  
S. A. de Araujo ◽  
A. C. Cherri
Keyword(s):  
Lot Sizing ◽  
Cutting Stock Problem ◽  
Cutting Stock ◽  
One Dimensional

scholarly journals COMPARISON OF MIP MODELS FOR THE INTEGRATED LOT-SIZING AND ONE-DIMENSIONAL CUTTING STOCK PROBLEM

2016 ◽  
Vol 36 (1) ◽  
pp. 167-196 ◽  
Author(s):  
Gislaine Mara Melega ◽  
Silvio Alexandre de Araujo ◽  
Raf Jans
Keyword(s):  
Lot Sizing ◽  
Cutting Stock Problem ◽  
Cutting Stock ◽  
One Dimensional ◽  
Mip Models

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.

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