Semi-infinite relaxation of joint chance constraints in chance-constrained programming Part 1. Zero-order stochastic decision rules† |
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| Authors: | A CHARNES Y C CHANG J SEMPLE |
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| Affiliation: | 1. Center for Cybernetic Studies, College of Business Administration , University of Texas at Austin , Austin, Texas, 5.202, U.S.A.;2. Center for Cybernetic Studies , The University of Texas at Austin and The Wyatt Company , Dallas, Texas, U.S.A. |
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| Abstract: | A new class of semi-infinite deterministic (‘determinizations’) dominants and relaxations of joint chance-constraints in chance-constrained programming is developed and specialized to zero-order stochastic decision rule situations. Tight constraint relaxations are obtained where only the partial information of means and variances is known. The tight non-linear semi-infinite relaxations are related to an accessible finite subsystem. When the chance constraints involve linear inequalities, for a large class, the non-linear tight system is proved equivalent to a linear program. Its solutions for the Prekopa-Szantai reservoir construction examples agree well with theirs |
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