A Brief Overview of Interdiction and Robust Optimization

Leonardo Lozano, J. Cole Smith

Research output: Chapter in Book/Report/Conference proceedingChapter

Abstract

Two-player optimization problems span an impressive array of possible situations, including cases in which both players optimize their own objective with no regard for the other’s goals, or in which one agent seeks to impede the other’s objective. The agents may commit their decisions simultaneously, using either deterministic or random (mixed) strategies. Alternatively, they can play them in sequence, where one agent has complete or partial knowledge of the other’s decisions. This overview provides the reader insights and entry points into learning about two-stage zero-sum games (e.g., minimax or maximin) in which one agent has complete knowledge of the other’s actions. The difference between interdiction and robust optimization models is described, with a focus on steering the reader to relevant and contemporary research in the field.

Original languageEnglish (US)
Title of host publicationSpringer Optimization and Its Applications
PublisherSpringer
Pages33-39
Number of pages7
DOIs
StatePublished - Jan 1 2019
Externally publishedYes

Publication series

NameSpringer Optimization and Its Applications
Volume152
ISSN (Print)1931-6828
ISSN (Electronic)1931-6836

ASJC Scopus subject areas

  • Control and Optimization

Fingerprint Dive into the research topics of 'A Brief Overview of Interdiction and Robust Optimization'. Together they form a unique fingerprint.

  • Cite this

    Lozano, L., & Smith, J. C. (2019). A Brief Overview of Interdiction and Robust Optimization. In Springer Optimization and Its Applications (pp. 33-39). (Springer Optimization and Its Applications; Vol. 152). Springer. https://doi.org/10.1007/978-3-030-28565-4_7