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A mathematical programming approach to identification and optimization of a class of unknown systems

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  • Charles A. Holloway

Abstract

There exists a class of decision problems for which: (1) models of input‐output response functions are not available in a closed‐form, functional representation; (2) informational costs associated with learning about the response function are significant. For these problems, combining identification with optimization using mathematical programming is potentially attractive. Three approaches to the identification‐optimization problem are proposed: an outer‐linearized approximation using relaxation (OLR); an inner‐linearized approximation using restriction (ILR); and a sequential combination of inner‐ and outer‐linearized subproblems (SIO). Algorithms based on each approach are developed and computational experience reported.

Suggested Citation

  • Charles A. Holloway, 1972. "A mathematical programming approach to identification and optimization of a class of unknown systems," Naval Research Logistics Quarterly, John Wiley & Sons, vol. 19(4), pages 663-679, December.
    • Handle: RePEc:wly:navlog:v:19:y:1972:i:4:p:663-679
    DOI: 10.1002/nav.3800190407
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