Solving a combined cutting-stock and lot-sizing problem with a column generating procedure

2008 ◽  
Vol 35 (10) ◽  
pp. 3371-3392 ◽  
Author(s):  
Sigrid Lise NonÅs ◽  
Anders Thorstenson
2016 ◽  
Vol 17 (3) ◽  
pp. 305 ◽  
Author(s):  
Sônia Cristina Poltroniere ◽  
Silvio Alexandre Araujo ◽  
Kelly Cristina Poldi

Two important optimization problems occur in the planning and production scheduling in paper industries: the lot sizing problem and the cutting stock problem. The lot sizing problem must determine the quantity of jumbos of different types of paper to be produced in each machine over a finite planning horizon.These jumbos are then cut in order to meet the demand of items for each period. In this paper, we deal with the integration of these two problems, aiming to minimize costs of production and in- ventory of jumbos, as well as the trim loss of paper generated during the cutting process. Two mathematical models for the integrated problem are considered, and these models are solved both heuristically and using an optimization package. Attempting to get lower bounds for the problem, relaxed versions of the models also have been solved. Finally, computational experiments are presented and discussed. 


2000 ◽  
Vol 120 (2) ◽  
pp. 327-342 ◽  
Author(s):  
Sigrid Lise Nonås ◽  
Anders Thorstenson

2007 ◽  
Vol 157 (1) ◽  
pp. 91-104 ◽  
Author(s):  
Sônia Cristina Poltroniere ◽  
Kelly Cristina Poldi ◽  
Franklina Maria Bragion Toledo ◽  
Marcos Nereu Arenales

2018 ◽  
Vol 95 ◽  
pp. 44-55 ◽  
Author(s):  
Ning Ma ◽  
Ya Liu ◽  
Zhili Zhou ◽  
Chengbin Chu

2019 ◽  
Vol 4 (2) ◽  
pp. 205-214
Author(s):  
Erika Fatma

Lot sizing problem in production planning aims to optimize production costs (processing, setup and holding cost) by fulfilling demand and resources capacity costraint. The Capacitated Lot sizing Problem (CLSP) model aims to balance the setup costs and inventory costs to obtain optimal total costs. The object of this study was a plastic component manufacturing company. This study use CLSP model, considering process costs, holding costs and setup costs, by calculating product cycle and setup time. The constraint of this model is the production time capacity and the storage capacity of the finished product. CLSP can reduce the total production cost by 4.05% and can reduce setup time by 46.75%.  Keyword: Lot size, CLSP, Total production cost.


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