Approximating Joint Chance Constraints in Two-Stage Stochastic Programs
- Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
We present various approximations to joint chance constraints arising in two-stage stochastic programming models. Our approximations are derived from three classical inequalities: Markov's inequality, Chebysev's inequality, and Chernoff's bound. We provide preliminary computational results illustrating the quality of our approximation using a two-stage joint-chance-constrained stochastic program from the literature. We also briefly introduce other alternatives for constructing approximations for joint-chance-constrained two-stage programs.
- Research Organization:
- Sandia National Laboratories (SNL-NM), Albuquerque, NM (United States)
- Sponsoring Organization:
- USDOE National Nuclear Security Administration (NNSA)
- DOE Contract Number:
- AC04-94AL85000; NA0003525
- OSTI ID:
- 1763205
- Report Number(s):
- SAND--2019-10028R; 678816
- Country of Publication:
- United States
- Language:
- English
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