Bottlenecks with respect to due-time performance in pull serial production lines.
Bottom-up learning of hierarchical models in a class of deterministic POMDP environments
The theory of partially observable Markov decision processes (POMDPs) is a useful tool for developing various intelligent agents, and learning hierarchical POMDP models is one of the key approaches for building such agents when the environments of the agents are unknown and large. To learn hierarchical models, bottom-up learning methods in which learning takes place in a layer-by-layer manner from the lowest to the highest layer are already extensively used in some research fields such as hidden...
Boundary-influenced robust controls: two network examples
We consider the differential game associated with robust control of a system in a compact state domain, using Skorokhod dynamics on the boundary. A specific class of problems motivated by queueing network control is considered. A constructive approach to the Hamilton-Jacobi-Isaacs equation is developed which is based on an appropriate family of extremals, including boundary extremals for which the Skorokhod dynamics are active. A number of technical lemmas and a structured verification theorem...
Bound-based decision rules in multistage stochastic programming
We study bounding approximations for a multistage stochastic program with expected value constraints. Two simpler approximate stochastic programs, which provide upper and lower bounds on the original problem, are obtained by replacing the original stochastic data process by finitely supported approximate processes. We model the original and approximate processes as dependent random vectors on a joint probability space. This probabilistic coupling allows us to transform the optimal solution of the...
Bounded diagonally stationary sequences in convex optimization.
Bounded expansion in web graphs
In this paper we study various models for web graphs with respect to bounded expansion. All the deterministic models even have constant expansion, whereas the copying model has unbounded expansion. The most interesting case turns out to be the preferential attachment model --- which we conjecture to have unbounded expansion, too.
Bounded linear regularity, strong CHIP, and CHIP are distinct properties.
Bounds for aggregated solid transportation problem and an improved disaggregation method
Bounds of the affine breadth eccentricity of convex bodies via semi-infinite optimization.
Bounds on discrete dynamic programming recursions. I. Models with non-negative matrices
Bounds on discrete dynamic programming recursions. II. Polynomial bounds on problems with block-triangular structure
Bounds on integrals with respect to multivariate copulas
In this paper, we present a method to obtain upper and lower bounds on integrals with respect to copulas by solving the corresponding assignment problems (AP’s). In their 2014 paper, Hofer and Iacó proposed this approach for two dimensions and stated the generalization to arbitrary dimensons as an open problem. We will clarify the connection between copulas and AP’s and thus find an extension to the multidimensional case. Furthermore, we provide convergence statements and, as applications, we consider...
Bounds on the throughput of an unslotted ALOHA channel in the case of a heterogeneous users' population
Branch and Cut based on the volume algorithm: Steiner trees in graphs and Max-cut
We present a Branch-and-Cut algorithm where the volume algorithm is applied instead of the traditionally used dual simplex algorithm to the linear programming relaxations in the root node of the search tree. This means that we use fast approximate solutions to these linear programs instead of exact but slower solutions. We present computational results with the Steiner tree and Max-Cut problems. We show evidence that one can solve these problems much faster with the volume algorithm based...
Branch-and-bound algorithm for total weighted tardiness minimization on parallel machines under release dates assumptions
This paper deals with the parallel-machine scheduling problem with the aim of minimizing the total (weighted) tardiness under the assumption of different release dates. This problem has been proven to be NP-hard. We introduce some new lower and upper bounds based on different approaches. We propose a branch-and-bound algorithm to solve the weighted and unweighted total tardiness. Computational experiments were performed on a large set of instances...
Branch-and-bound algorithm for total weighted tardiness minimization on parallel machines under release dates assumptions
This paper deals with the parallel-machine scheduling problem with the aim of minimizing the total (weighted) tardiness under the assumption of different release dates. This problem has been proven to be NP-hard. We introduce some new lower and upper bounds based on different approaches. We propose a branch-and-bound algorithm to solve the weighted and unweighted total tardiness. Computational experiments were performed on a large set of instances...
Bregman distances, totally convex functions, and a method for solving operator equations in Banach spaces.
Brève communication. Application de la théorie des potentiels au projet d'un barrage
Brève communication. Décomposition en programmation convexe
Brève communication. Méthode de l'état adjoint par «relaxation»