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The risk-sensitive Poisson equation for a communicating Markov chain on a denumerable state space

Rolando Cavazos-Cadena (2009)

Kybernetika

This work concerns a discrete-time Markov chain with time-invariant transition mechanism and denumerable state space, which is endowed with a nonnegative cost function with finite support. The performance of the chain is measured by the (long-run) risk-sensitive average cost and, assuming that the state space is communicating, the existence of a solution to the risk-sensitive Poisson equation is established, a result that holds even for transient chains. Also, a sufficient criterion ensuring that...

The second order optimality conditions for nonlinear mathematical programming with C 1 , 1 data

Liping Liu, Michal Křížek (1997)

Applications of Mathematics

To find nonlinear minimization problems are considered and standard C 2 -regularity assumptions on the criterion function and constrained functions are reduced to C 1 , 1 -regularity. With the aid of the generalized second order directional derivative for C 1 , 1 real-valued functions, a new second order necessary optimality condition and a new second order sufficient optimality condition for these problems are derived.

The single (and multi) item profit maximizing capacitated lot–size (PCLSP) problem with fixed prices and no set–up

Kjetil K. Haugen, Asmund Olstad, Krystsina Bakhrankova, Erik Van Eikenhorst (2010)

Kybernetika

This paper proposes a specialized LP-algorithm for a sub problem arising in simple Profit maximising Lot-sizing. The setting involves a single (and multi) item production system with negligible set-up costs/times and limited production capacity. The producer faces a monopolistic market with given time-varying linear demand curves.

The steepest descent dynamical system with control. Applications to constrained minimization

Alexandre Cabot (2004)

ESAIM: Control, Optimisation and Calculus of Variations

Let H be a real Hilbert space, Φ 1 : H a convex function of class 𝒞 1 that we wish to minimize under the convex constraint S . A classical approach consists in following the trajectories of the generalized steepest descent system (cf. Brézis [5]) applied to the non-smooth function Φ 1 + δ S . Following Antipin [1], it is also possible to use a continuous gradient-projection system. We propose here an alternative method as follows: given a smooth convex function Φ 0 : H whose critical points coincide with S and a control...

The steepest descent dynamical system with control. Applications to constrained minimization

Alexandre Cabot (2010)

ESAIM: Control, Optimisation and Calculus of Variations

Let H be a real Hilbert space, Φ 1 : H a convex function of class 𝒞 1 that we wish to minimize under the convex constraint S. A classical approach consists in following the trajectories of the generalized steepest descent system (cf.   Brézis [CITE]) applied to the non-smooth function  Φ 1 + δ S . Following Antipin [1], it is also possible to use a continuous gradient-projection system. We propose here an alternative method as follows: given a smooth convex function  Φ 0 : H whose critical points coincide with S and...

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