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| Author(s): |
Douglas José Alem Junior
Total Authors: 1
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| Document type: | Master's Dissertation |
| Press: | São Carlos. |
| Institution: | Universidade de São Paulo (USP). Instituto de Ciências Matemáticas e de Computação (ICMC/SB) |
| Defense date: | 2007-03-22 |
| Examining board members: |
Marcos Nereu Arenales;
Paulo Augusto Valente Ferreira;
Robinson Samuel Vieira Hoto
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| Advisor: | Marcos Nereu Arenales |
| Abstract | |
This paper presents an integer linear optimization model of large scale for the one-dimensional cutting stock problem in the case which a demand is considered a random variable. To take this randomness into account, the problem was formulated as a two-stage stochastic linear program with recourse. The first stage decision variables are given by the number of bars that has to be cut according to each pattern, and the second stage decision variables by the number of holding items or backordering items production. The model objective is minimizes the total expected cost. We propose two methods to solve the model linear relaxation, one of them it is a Simplex-based method with column generation. The second method is a heuristic strategy that adopted the expected value of demand. We compare both strategies and the possibly of ignoring uncertainties on model. Finally, we observe that is much more interesting to determine the optimal recourse model solution when we have problems that are more afected by randomness (AU) | |