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Reformulation of the Multiperiod MILP Model for Capacity Expansion of Chemical Processes

Author

Listed:
  • N. V. Sahinidis

    (Carnegie Mellon University, Pittsburgh, Pennsylvania)

  • I. E. Grossmann

    (Carnegie Mellon University, Pittsburgh, Pennsylvania)

Abstract

The problem of selecting processes and capacity expansion policies for a chemical complex consisting of continuous chemical processes can be formulated as a multiperiod, mixed integer linear programming (MILP) problem. Based on a variable disaggregation technique which exploits lot sizing substructures, we propose two reformulations of the conventional MILP model. The first one is an NLP reformulation which very quickly yields good suboptimal solutions. The second is an MILP reformulation for exact solutions which leads to up to an order of magnitude faster computational results for large problems due to its tighter linear programming relaxation.

Suggested Citation

  • N. V. Sahinidis & I. E. Grossmann, 1992. "Reformulation of the Multiperiod MILP Model for Capacity Expansion of Chemical Processes," Operations Research, INFORMS, vol. 40(1-supplem), pages 127-144, February.
    • Handle: RePEc:inm:oropre:v:40:y:1992:i:1-supplement-1:p:s127-s144
    DOI: 10.1287/opre.40.1.S127
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    Cited by:

    1. Francisco Barahona & Stuart Bermon & Oktay Günlük & Sarah Hood, 2005. "Robust capacity planning in semiconductor manufacturing," Naval Research Logistics (NRL), John Wiley & Sons, vol. 52(5), pages 459-468, August.
    2. Ogbe, Emmanuel & Li, Xiang, 2017. "A new cross decomposition method for stochastic mixed-integer linear programming," European Journal of Operational Research, Elsevier, vol. 256(2), pages 487-499.
    3. Martínez-Costa, Carme & Mas-Machuca, Marta & Benedito, Ernest & Corominas, Albert, 2014. "A review of mathematical programming models for strategic capacity planning in manufacturing," International Journal of Production Economics, Elsevier, vol. 153(C), pages 66-85.
    4. Huang, Kai & Ahmed, Shabbir, 2010. "A stochastic programming approach for planning horizons of infinite horizon capacity planning problems," European Journal of Operational Research, Elsevier, vol. 200(1), pages 74-84, January.
    5. Zhouchun Huang & Qipeng P. Zheng & Andrew L. Liu, 2022. "A Nested Cross Decomposition Algorithm for Power System Capacity Expansion with Multiscale Uncertainties," INFORMS Journal on Computing, INFORMS, vol. 34(4), pages 1919-1939, July.
    6. Bennett, Derek P. & Yano, Candace A., 2004. "A decomposition approach for an equipment selection and multiple product routing problem incorporating environmental factors," European Journal of Operational Research, Elsevier, vol. 156(3), pages 643-664, August.
    7. M. Gonçalves & J. Melo & L. Prudente, 2015. "Augmented Lagrangian methods for nonlinear programming with possible infeasibility," Journal of Global Optimization, Springer, vol. 63(2), pages 297-318, October.
    8. Shabbir Ahmed & Nikolaos V. Sahinidis, 2003. "An Approximation Scheme for Stochastic Integer Programs Arising in Capacity Expansion," Operations Research, INFORMS, vol. 51(3), pages 461-471, June.

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