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An Improved Heuristic Procedure for a Nonlinear Cutting Stock Problem

Author

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  • I. Coverdale

    (University of Hull, England)

  • F. Wharton

    (University of Hull, England)

Abstract

Many industries acquire stocks of material in large standard sizes which are then reduced to required widths or lengths according to demand. Scheduling the cutting operations is a particularly difficult problem when a few cutting patterns must be chosen from a vast number of feasible patterns such that the total cost of the reduction process is minimised. Physical constraints and economic considerations restrict the number and type of pattern which can be used. Haessler [Haessiler, R. W. An application of heuristic programming to a nonlinear cutting-stock problem occurring in the paper industry. Unpublished doctoral dissertation, The University of Michigan, Ann Arbor, 1968, available through University Microfilms, Ann Arbor, Dissertation No. 69-12, 119; Haessiler, R. W. 1971. A heuristic programming solution to a nonlinear cutting-stock problem. Management Sci. 17 (12, August) 793-802.] has described a typical problem in the paper industry and a heuristic procedure for obtaining satisfactory schedules. An improved procedure is proposed in which the type of pattern generated and accepted into the schedule is constrained to improve the likelihood that the residual scheduling problem has a feasible and economic solution. Results obtained by the proposed procedure are compared with those obtained manually and by Haessler for a set of eleven actual problems.

Suggested Citation

  • I. Coverdale & F. Wharton, 1976. "An Improved Heuristic Procedure for a Nonlinear Cutting Stock Problem," Management Science, INFORMS, vol. 23(1), pages 78-86, September.
    • Handle: RePEc:inm:ormnsc:v:23:y:1976:i:1:p:78-86
    DOI: 10.1287/mnsc.23.1.78
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    Cited by:

    1. Maimon, Oded & Dayagi, Arie, 1995. "Nesting planning based on production priorities and technological efficiency," European Journal of Operational Research, Elsevier, vol. 80(1), pages 121-129, January.
    2. Song, X. & Chu, C.B. & Nie, Y.Y. & Bennell, J.A., 2006. "An iterative sequential heuristic procedure to a real-life 1.5-dimensional cutting stock problem," European Journal of Operational Research, Elsevier, vol. 175(3), pages 1870-1889, December.
    3. Westerlund, Tapio & Isaksson, Johnny & Harjunkoski, Iiro, 1998. "Solving a two-dimensional trim-loss problem with MILP," European Journal of Operational Research, Elsevier, vol. 104(3), pages 572-581, February.
    4. Harjunkoski, Iiro & Westerlund, Tapio & Porn, Ray & Skrifvars, Hans, 1998. "Different transformations for solving non-convex trim-loss problems by MINLP," European Journal of Operational Research, Elsevier, vol. 105(3), pages 594-603, March.
    5. Nonas, Sigrid Lise & Thorstenson, Anders, 2000. "A combined cutting-stock and lot-sizing problem," European Journal of Operational Research, Elsevier, vol. 120(2), pages 327-342, January.
    6. Tao Wu & Kerem Akartunal? & Raf Jans & Zhe Liang, 2017. "Progressive Selection Method for the Coupled Lot-Sizing and Cutting-Stock Problem," INFORMS Journal on Computing, INFORMS, vol. 29(3), pages 523-543, August.

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