Robust linear semi-infinite programming duality under uncertainty

In this paper, we propose a duality theory for semi-infinite linear programming problems under uncertainty in the constraint functions, the objective function, or both, within the framework of robust optimization. We present robust duality by establishing strong duality between the robust counterpart of an uncertain semi-infinite linear program and the optimistic counterpart of its uncertain Lagrangian dual. We show that robust duality holds whenever a robust moment cone is closed and convex. We then establish that the closed-convex robust moment cone condition in the case of constraint-wise uncertainty is in fact necessary and sufficient for robust duality. In other words, the robust moment cone is closed and convex if and only if robust duality holds for every linear objective function of the program. In the case of uncertain problems with affinely parameterized data uncertainty, we establish that robust duality is easily satisfied under a Slater type constraint qualification. Consequently, we derive robust forms of the Farkas lemma for systems of uncertain semi-infinite linear inequalities.

Fermi-edge singularities in linear and nonlinear ultrafast spectroscopy

We discuss Fermi-edge singularity effects on the linear and nonlinear transient response of an electron gas in a doped semiconductor. We use a bosonization scheme to describe the low-energy excitations, which allows us to compute the time and temperature dependence of the response functions. Coherent control of the energy absorption at resonance is analyzed in the linear regime. It is shown that a phase shift appears in the coherent control oscillations, which is not present in the excitonic case. The nonlinear response is calculated analytically and used to predict that four wave-mixing experiments would present a Fermi-edge singularity when the exciting energy is varied. A new dephasing mechanism is predicted in doped samples that depends linearly on temperature and is produced by the low-energy bosonic excitations in the conduction band.

Quantitative stability of linear infinite inequality systems under block perturbations with applications to convex systems

The original motivation for this paper was to provide an efficient quantitative analysis of convex infinite (or semi-infinite) inequality systems whose decision variables run over general infinite-dimensional (resp. finite-dimensional) Banach spaces and that are indexed by an arbitrary fixed set J. Parameter perturbations on the right-hand side of the inequalities are required to be merely bounded, and thus the natural parameter space is l ∞(J). Our basic strategy consists of linearizing the parameterized convex system via splitting convex inequalities into linear ones by using the Fenchel–Legendre conjugate. This approach yields that arbitrary bounded right-hand side perturbations of the convex system turn on constant-by-blocks perturbations in the linearized system. Based on advanced variational analysis, we derive a precise formula for computing the exact Lipschitzian bound of the feasible solution map of block-perturbed linear systems, which involves only the system’s data, and then show that this exact bound agrees with the coderivative norm of the aforementioned mapping. In this way we extend to the convex setting the results of Cánovas et al. (SIAM J. Optim. 20, 1504–1526, 2009) developed for arbitrary perturbations with no block structure in the linear framework under the boundedness assumption on the system’s coefficients. The latter boundedness assumption is removed in this paper when the decision space is reflexive. The last section provides the aimed application to the convex case.

Robust Solutions of MultiObjective Linear Semi-Infinite Programs under Constraint Data Uncertainty

The multiobjective optimization model studied in this paper deals with simultaneous minimization of finitely many linear functions subject to an arbitrary number of uncertain linear constraints. We first provide a radius of robust feasibility guaranteeing the feasibility of the robust counterpart under affine data parametrization. We then establish dual characterizations of robust solutions of our model that are immunized against data uncertainty by way of characterizing corresponding solutions of robust counterpart of the model. Consequently, we present robust duality theorems relating the value of the robust model with the corresponding value of its dual problem.

Predicting water permeability in sedimentary rocks from capillary imbibition and pore structure

In this paper, absolute water permeability is estimated from capillary imbibition and pore structure for 15 sedimentary rock types. They present a wide range of petrographic characteristics that provide degrees of connectivity, porosities, pore size distributions, water absorption coefficients by capillarity and water permeabilities. A statistical analysis shows strong correlations among the petrophysical parameters of the studied rocks. Several fundamental properties are fitted into different linear and multiple expressions where water permeability is expressed as a generalized function of the properties. Some practical aspects of these correlations are highlighted in order to use capillary imbibition tests to estimate permeability. The permeability–porosity relation is discussed in the context of the influence of pore connectivity and wettability. As a consequence, we propose a generalized model for permeability that includes information about water fluid rate (water absorption coefficient by capillarity), water properties (density and viscosity), wetting (interfacial tension and contact angle) and pore structure (pore radius and porosity). Its application is examined in terms of the type of pores that contribute to water transport and wettability. The results indicate that the threshold pore radius, in which water percolates through rock, achieves the best description of the pore system. The proposed equation is compared against Carman–Kozeny's and Katz–Thompson's equations. The proposed equation achieves very accurate predictions of the water permeability in the range of 0.01 to 1000 mD.