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Base-2 Expansions for Linearizing Products of Functions of Discrete Variables

Author

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  • Warren P. Adams

    (Department of Mathematical Sciences, Clemson University, Clemson, South Carolina 29634)

  • Stephen M. Henry

    (System Readiness and Sustainment Technologies Group, Sandia National Laboratories, Albuquerque, New Mexico 87123)

Abstract

This paper presents an approach for representing functions of discrete variables, and their products, using logarithmic numbers of binary variables. Given a univariate function whose domain consists of n distinct values, it begins by employing a base-2 expansion to express the function in terms of the ceiling of log 2 n binary and n continuous variables, using linear restrictions to equate the functional values with the possible binary realizations. The representation of the product of such a function with a nonnegative variable is handled via an appropriate scaling of the linear restrictions. Products of m functions are treated in an inductive manner from i = 2 to m , where each step i uses such a scaling to express the product of function i and a nonnegative variable denoting a translated version of the product of functions 1 through i - 1 as a newly defined variable. The resulting representations, both in terms of one function and many, are important for reformulating general discrete variables as binary, and also for linearizing mixed-integer generalized geometric and discrete nonlinear programs, where it is desired to economize on the number of binary variables. The approach provides insight into, improves upon, and subsumes related linearization methods for products of functions of discrete variables.

Suggested Citation

  • Warren P. Adams & Stephen M. Henry, 2012. "Base-2 Expansions for Linearizing Products of Functions of Discrete Variables," Operations Research, INFORMS, vol. 60(6), pages 1477-1490, December.
  • Handle: RePEc:inm:oropre:v:60:y:2012:i:6:p:1477-1490
    DOI: 10.1287/opre.1120.1106
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    References listed on IDEAS

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    Cited by:

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    2. Hao-Chun Lu, 2017. "Improved logarithmic linearizing method for optimization problems with free-sign pure discrete signomial terms," Journal of Global Optimization, Springer, vol. 68(1), pages 95-123, May.
    3. Joey Huchette & Joey Huchette, 2019. "A Combinatorial Approach for Small and Strong Formulations of Disjunctive Constraints," Mathematics of Operations Research, INFORMS, vol. 44(3), pages 793-820, August.
    4. Han-Lin Li & Yao-Huei Huang & Shu-Cherng Fang, 2017. "Linear Reformulation of Polynomial Discrete Programming for Fast Computation," INFORMS Journal on Computing, INFORMS, vol. 29(1), pages 108-122, February.
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    6. Qi An & Shu-Cherng Fang & Tiantian Nie & Shan Jiang, 2018. "$$\ell _1$$ ℓ 1 -Norm Based Central Point Analysis for Asymmetric Radial Data," Annals of Data Science, Springer, vol. 5(3), pages 469-486, September.
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    8. M. Hosein Zare & Juan S. Borrero & Bo Zeng & Oleg A. Prokopyev, 2019. "A note on linearized reformulations for a class of bilevel linear integer problems," Annals of Operations Research, Springer, vol. 272(1), pages 99-117, January.
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