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Finite algorithm for generalized linear multiplicative programming

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Abstract

The nonconvex problem of minimizing the sum of a linear function and the product of two linear functions over a convex polyhedron is considered. A finite algorithm is proposed which either finds a global optimum or shows that the objective function is unbounded from below in the feasible region. This is done by means of a sequence of primal and/or dual simplex iterations.

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Authors and Affiliations

  1. Graduate School of Management, University of California, Riverside, California

    S. Schaible (Professor)

  2. Dipartimento di Statistica e Matematica Applicata all'Economia, Facolta' di Economia, Universitá di Pisa, Pisa, Italy

    C. Sodini (Professor)

Authors
  1. S. Schaible
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  2. C. Sodini
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Additional information

The first author gratefully acknowledges the research support received as Visiting Professor of the Dipartimento di Statistica e Matematica Applicata all' Economia, Universitá di Pisa, Pisa, Italy, Spring 1992.

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Schaible, S., Sodini, C. Finite algorithm for generalized linear multiplicative programming. J Optim Theory Appl 87, 441–455 (1995). https://doi.org/10.1007/BF02192573

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  • DOI: https://doi.org/10.1007/BF02192573

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