Interval methods for semi-infinite programs

  • Authors:

  • Binita Bhattacharjee;William H. Green, Jr.;Paul I. Barton

  • Affiliations:

  • Massachusetts Institute of Technology 66-464, 77 Massachusetts Avenue, Cambridge, MA;Massachusetts Institute of Technology 66-464, 77 Massachusetts Avenue, Cambridge, MA;Massachusetts Institute of Technology 66-464, 77 Massachusetts Avenue, Cambridge, MA

  • Venue:
  • Computational Optimization and Applications
  • Year:
  • 2005

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Abstract

A new approach for the numerical solution of smooth, nonlinear semi-infinite programs whose feasible set contains a nonempty interior is presented. Interval analysis methods are used to construct finite nonlinear, or mixed-integer nonlinear, reformulations of the original semi-infinite program under relatively mild assumptions on the problem structure. In certain cases the finite reformulation is exact and can be solved directly for the global minimum of the semi-infinite program (SIP). In the general case, this reformulation is over-constrained relative to the SIP, such that solving it yields a guaranteed feasible upper bound to the SIP solution. This upper bound can then be refined using a subdivision procedure which is shown to converge to the true SIP solution with finite ε-optimality. In particular, the method is shown to converge for SIPs which do not satisfy regularity assumptions required by reduction-based methods, and for which certain points in the feasible set are subject to an infinite number of active constraints. Numerical results are presented for a number of problems in the SIP literature. The solutions obtained are compared to those identified by reduction-based methods, the relative performances of the nonlinear and mixed-integer nonlinear formulations are studied, and the use of different inclusion functions in the finite reformulation is investigated.