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Application of optimization for solving a sawing stock problem with a cant sawing pattern

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Abstract

This paper introduces an optimization approach for solving the sawing stock problem in a sawmill in Brazil using the cant sawing pattern, in which lateral and central pieces are cut from the log surface. As this problem has been proved NP-hard and involves some nonlinearities due to the circular geometry of this pattern, we developed a solution method based on two stages. First, we developed an algorithm to generate all sawing patterns, considering the available log diameters and the demanded lumbers. Next, two integer linear programming models were formulated to optimize the number of sawing patterns to be cut, fulfilling the demand in the planning horizon and attending the amount of logs in inventory. One model minimizes the wood loss, while the other maximizes the sales revenue. The optimization approach was evaluated using real data from the sawmill, obtaining significant reductions in the volume cut, in comparison with the current manual planning process, while completely fulfilling the demand.

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Acknowledgements

The authors would like to thank the anonymous referees for improving the quality of the paper. This research was partially founded by CNPq, Brazil.

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Authors and Affiliations

  1. Management School, Universidade Federal do Rio Grande do Sul, Porto Alegre, RS, Brazil

    Juan Leandro Andres Parra Galvez & Denis Borenstein

  2. Interdisciplinary Department, Campus Litoral Norte, Federal University of Rio Grande do Sul, Tramandaí, RS, Brazil

    Everton da Silveira Farias

Authors
  1. Juan Leandro Andres Parra Galvez
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  2. Denis Borenstein
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  3. Everton da Silveira Farias
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Correspondence to Denis Borenstein.

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Parra Galvez, J.L.A., Borenstein, D. & da Silveira Farias, E. Application of optimization for solving a sawing stock problem with a cant sawing pattern. Optim Lett 12, 1755–1772 (2018). https://doi.org/10.1007/s11590-017-1178-x

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  • DOI: https://doi.org/10.1007/s11590-017-1178-x

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