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Technical Note—Generalized Covering Relaxation for 0-1 Programs

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  • Daniel Granot

    (University of British Columbia, Vancouver, Canada)

  • Frieda Granot

    (University of British Columbia, Vancouver, Canada)

Abstract

We construct in this paper a general purpose cutting-plane algorithm for solving the 0-1 polynomial programming problem of finding a 0-1 n vector x = ( x j ) that maximizes c T x subject to f ( x ) ≤ b where f ( x ) = ( f i ( x )) is an m vector of polynomials. The algorithm consists of solving a nested sequence of linear generalized covering problems, i.e., covering problems involving both the original variables x and their complements x̄ = 1 − x . Each problem in the sequence is a relaxation of the original 0-1 polynomial program, and is obtained by adding to its predecessor a small number of generalized covering constraints that are violated by the optimal solution for the preceding generalized covering problem. Over 95% of more than 800 randomly generated problems with up to 70 variables and 50 constraints and mostly up to 5 terms in each constraint were solved by our method in less than 90 seconds of CPU time on an AMDAHL 470 V-6 computer.

Suggested Citation

  • Daniel Granot & Frieda Granot, 1980. "Technical Note—Generalized Covering Relaxation for 0-1 Programs," Operations Research, INFORMS, vol. 28(6), pages 1442-1450, December.
    • Handle: RePEc:inm:oropre:v:28:y:1980:i:6:p:1442-1450
    DOI: 10.1287/opre.28.6.1442
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