β Scribed by Bernard Fortz; Michael Poss
No coin nor oath required. For personal study only.
We show how we can linearize individual probabilistic linear constraints with binary variables when all coefficients are independently distributed according to either N (¡ i , λ¡ i ), for some λ > 0 and ¡ i > 0, or Π(k i , θ ) for some θ > 0 and k i > 0. The constraint can also be linearized when the coefficients are independent and identically distributed and either positive or strictly stable random variables.
π SIMILAR VOLUMES
In this paper we generalize the concepts of well-posedness to equilibrium problems and to optimization problems with equilibrium constraints. We establish some metric characterizations of well-posedness for equilibrium problems and for optimization problems with equilibrium constraints. We prove tha
Gi¨en a null-filled radiation power pattern to be synthesized by a linear antenna array, optimally realizable excitation distributions satisfying the requirements of being symmetric or in phase can be found by means of a genetic algorithm approach.
## Abstract In this paper we derive sufficient conditions for optimal control problems with mixed control and state constraints by applying a dual approach to the dynamic programming. These conditions guarantee that a relative minimum is achieved. We seek an optimal pair in the class of those admis