Stochastic optimization in supply chain networks: averaging robust solutions

We propose a novel robust optimization approach to analyze and optimize the expected performance of supply chain networks. We model uncertainty in the dema     

Some Remark on Optimal Stochastic Control with Partial Information

Abstract

We are interested in the control problem of a partially observable diffusion process, which is initialized at a fixed point of ? ⁿ , and we want to characterize the associated value function. To resort to the theory of viscosity solutions depends on the possibility to translate such a problem on Hilbert spaces like L ²(? ⁿ ), and so it can not be used here. Nevertheless, a result of N. Bouleau and F. Hirsch allows us to introduce a broadened problem which fulfills the condition. The fact remains to link these two control problems.     

Combinatorial Optimization by Dynamic Contraction

A heuristic optimization methodology, Dynamic Contraction (DC), is introduced as an approach for solving a wide variety of hard combinatorial problems. Contraction is an operation that maps an instance of a problem to a smaller instance of the same problem. DC is an iterative improvement strategy that relies on contraction as a mechanism for escaping local minima. As a byproduct of contraction, efficiency is improved due to a reduction of problem size. Effectiveness of DC is shown through simple applications to two classical combinatorial problems: The graph bisection problem and the traveling salesman problem.     

A Struwe Type Decomposition Result for a Singular Elliptic Equation on Compact Riemannian Manifolds

On a compact Riemannian manifold,we prove a decomposition theorem for arbitrarily bounded energy sequence of solutions of a singular elliptic equation.     

On von Neumann regular elements in <Emphasis Type="Italic">f</Emphasis>-rings

Let B be an Archimedean reduced f-ring. A positive element \({\omega}\) in B is said to satisfy the property \({(\ast)}\) if for every f-ring A with identity e and every \({\ell}\)-group homomorphism \({\gamma : A \rightarrow B}\) with \({\gamma(e) = \omega}\), there exists a unique \({\ell}\)-ring homomorphism \({\rho: B \rightarrow B}\) such that \({\gamma = \omega \rho}\) and \({\rho(e)^{\perp \perp} = \omega^{\perp \perp}}\). Boulabiar and Hager proved that any (positive) von Neumann regular element in B satisfies the property \({(\ast)}\) and proved that the converse holds in the C(X)-case. In this regard, they asked about this converse in the general case. Our main purpose in this note is to prove, via a counter-example, that the converse in question fails in general. In addition, we shall take the opportunity to extend the direct result obtained by Boulabiar and Hager, and to get the C(X)-case we were talking about in an easier way.     

Resonance in Polyurea-Based Multilayer Structures Subjected to Laser-Generated Stress Waves

We report resonance associated with polyurea layers sandwiched between identical acrylic and polycarbonate plates when subjected to laser-generated stress waves of several nanoseconds in duration. Transmitted stress wave amplitudes almost 16 times the incident stress wave amplitudes are observed. An elastodynamics simulation identified the thickness of the polyurea layer as the key parameter controlling the amplitude of the transmitted stress wave. This resonance effect was found absent when the polyurea was sandwiched between the steel and aluminum plates of similar thickness. However, for these samples, a dramatic reduction in the amplitudes of the transmitted stress waves was recorded. A finite element analysis of the wave propagation through the sandwiched polyurea layer in these samples tied the large amplitude reduction to the large acoustic impedance mismatch and the viscoelastic dissipation within the polyurea layer.     

On clique relaxation models in network analysis

Increasing interest in studying community structures, or clusters in complex networks arising in various applications has led to a large and diverse body of literature introducing numerous graph-theoretic models relaxing certain characteristics of the classical clique concept. This paper analyzes the elementary clique-defining properties implicitly exploited in the available clique relaxation models and proposes a taxonomic framework that not only allows to classify the existing models in a systematic fashion, but also yields new clique relaxations of potential practical interest. Some basic structural properties of several of the considered models are identified that may facilitate the choice of methods for solving the corresponding optimization problems. In addition, bounds describing the cohesiveness properties of different clique relaxation structures are established, and practical implications of choosing one model over another are discussed.