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Global Optimization of Probabilistically Constrained Linear Programs

  • Shabbir Ahmed
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4204)

Abstract

Various applications in reliability and risk management give rise to optimization problems where certain constraints involve stochastic parameters and are required to be satisfied with a pre-specified probability threshold. In this talk we address such probabilistically constrained linear programs involving stochastic right-hand-sides. These problems involve non-convex feasible sets, and are extremely difficult to optimize.

Keywords

Global Optimization Convex Hull Mixed Integer Linear Program Global Optimal Solution Valid Inequality 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Shabbir Ahmed
    • 1
  1. 1.H. Milton Stewart School of Industrial & Systems EngineeringGeorgia Institute of Technology 

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