Disjonctions dans les ordonnancements
Diskrétní úlohy dynamického programování
Disponibilité d'un ensemble complexe
Distancias elipsoidales y puntos eficientes. Un método interactivo.
En este trabajo se estudian las propiedades que relacionan las distancias elipsoidales con la generación de puntos eficientes de un problema de programación multiobjetivo. Basándonos en estas propiedades, hemos construido un algoritmo interactivo convergente.
Distributed aggregative optimization with quantized communication
In this paper, we focus on an aggregative optimization problem under the communication bottleneck. The aggregative optimization is to minimize the sum of local cost functions. Each cost function depends on not only local state variables but also the sum of functions of global state variables. The goal is to solve the aggregative optimization problem through distributed computation and local efficient communication over a network of agents without a central coordinator. Using the variable tracking...
Distributed approach for solving time-dependent problems in multimodal transport networks.
Distributed dual averaging algorithm for multi-agent optimization with coupled constraints
This paper investigates a distributed algorithm for the multi-agent constrained optimization problem, which is to minimize a global objective function formed by a sum of local convex (possibly nonsmooth) functions under both coupled inequality and affine equality constraints. By introducing auxiliary variables, we decouple the constraints and transform the multi-agent optimization problem into a variational inequality problem with a set-valued monotone mapping. We propose a distributed dual averaging...
Distributed event-triggered algorithm for optimal resource allocation of multi-agent systems
This paper is concerned with solving the distributed resource allocation optimization problem by multi-agent systems over undirected graphs. The optimization objective function is a sum of local cost functions associated to individual agents, and the optimization variable satisfies a global network resource constraint. The local cost function and the network resource are the private data for each agent, which are not shared with others. A novel gradient-based continuous-time algorithm is proposed...
Distributed fuzzy decision making for production scheduling.
In production systems, input materials (educts) pass through multiple sequential stages until they become a product. The production stages consist of different machines with various dynamic characteristics. The coupling of those machines is a non-linear distributed system. With a distributed control system based on a multi-agent approach, the production system can achieve (almost) maximum output, where lot size and lot sequence are the most important control variables. In most production processes...
Distributed Nash equilibrium tracking via the alternating direction method of multipliers
Nash equilibrium is recognized as an important solution concept in non-cooperative game theory due to its broad applicability to economics, social sciences, computer science, and engineering. In view of its importance, substantial progress has been made to seek a static Nash equilibrium using distributed methods. However, these approaches are inapplicable in dynamic environments because, in this setting, the Nash equilibrium constantly changes over time. In this paper, we propose a dynamic algorithm...
Distributed optimization for multi-agent system over unbalanced graphs with linear convergence rate
Distributed optimization over unbalanced graphs is an important problem in multi-agent systems. Most of literatures, by introducing some auxiliary variables, utilize the Push-Sum scheme to handle the widespread unbalance graph with row or column stochastic matrix only. But the introduced auxiliary dynamics bring more calculation and communication tasks. In this paper, based on the in-degree and out-degree information of each agent, we propose an innovative distributed optimization algorithm to reduce...
Dobrushin's approach to queueing network theory.
Double pondération pour calculer une moyenne : Pourquoi et comment ?
L'opérateur de moyenne pondérée est très souvent utilisé pour définir une valeur v(a) à des entités a à partir de performances xj(a), j=1,...,n. Cet opérateur fait intervenir des poids spécifiqueswj comme multiplicateurs de la performance relative à la je composante. Ceci induit des possibilités de compensation des mauvaises performances par les meilleures qui peuvent être jugées inacceptables dans certains contextes concrets. En vue d'atténuer ces possibilités de compensation, on peut faire intervenir...
Doubly reflected BSDEs with call protection and their approximation
We study the numerical approximation of doubly reflected backward stochastic differential equations with intermittent upper barrier (RIBSDEs). These denote reflected BSDEs in which the upper barrier is only active on certain random time intervals. From the point of view of financial interpretation, RIBSDEs arise as pricing equations of game options with constrained callability. In a Markovian set-up we prove a convergence rate for a time-discretization scheme by simulation to an RIBSDE. We also...
DP2PN2Solver: A flexible dynamic programming solver software tool
Dual method for solving a special problem of quadratic programming as a subproblem at nonlinear minimax approximation
The paper describes the dual method for solving a special problem of quadratic programming as a subproblem at nonlinear minimax approximation. Two cases are analyzed in detail, differring in linear dependence of gradients of the active functions. The complete algorithm of the dual method is presented and its finite step convergence is proved.
Dual method for solving a special problem of quadratic programming as a subproblem at linearly constrained nonlinear minimax approximation
Dual of a linear fractional program through geometric programming
Dualidad de Haar y problemas de momentos.
En la primera parte de este trabajo damos una versión simplificada de la conocida relación entre la dualidad en Programación Semi-Infinita y cierta clase de problemas de momentos, basándonos en las propiedades de los sistemas de Farkas-Minkowski. Planteamos a continuación otra clase de problemas de momentos para cuyo análisis resulta de utilidad una generalización del Lema de Farkas.
Dualidad en la programación lineal en subconjuntos difusos.
La programación lineal sobre subconjuntos difusos, definida por Zimmermann, se desarrolla en estrecha relación con la definición de las funciones pertinentes funciones de pertenencia. Se estudia la dualidad difusa, ligada a la dualidad en los problemas de programación lineal con multicriterios.