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http://eprints.org/relation/isVersionOf https://pure.iiasa.ac.at/id/document/3295 http://eprints.org/relation/isVolatileVersionOf https://pure.iiasa.ac.at/id/document/3295 http://eprints.org/relation/isCoversheetVersionOf https://pure.iiasa.ac.at/id/document/3295 archive 351 disk0/00/00/32/54 2016-01-15 01:59:32 2021-08-27 17:13:32 2016-01-15 01:59:32 monograph show 2 Roemisch W. Schultz R. pub iis_met prog_ado Using results from parametric optimization we derive for chance constrained stochastic programs (quantitative) stability properties for (locally) optimal values and sets of (local) minimizers when the underlying probability distribution is subjected to perturbations. Emphasis is placed on verifiable sufficient conditions for the constraint-set-mapping to fulfill a Lipschitz property which is essential for the stability results. Both convex and non-convex problems are investigated. We present an optimal-load-dispatch model with considering the demand as a random vector and putting the equilibrium between total generation and demand as a probabilistic constraint. Since in optimal load dispatch the information on the probability distribution of the demand is often incomplete, we discuss consequences of our general results for the stability of optimal generation costs and optimal generation policies. 1989-11 published WP-89-090 WP-89-090 10 public working_paper IIASA, Laxenburg, Austria 26 FALSE info:eu-repo/semantics/book