Ant colony search algorithm for optimal generators startup during power system restoration.
Application de la théorie des graphes au choix des investissements à court terme dans un réseau électrique sujet à avaries
Application de l'optimisation en nombres entiers à un problème d'«arrondissage»
Application of ELECTRE III and DEA Methods in the Bpr of a Bank Branch Network
Application of non-linear programming to plane geometry.
Application of optimal transportation theory to the reconstruction of the early Universe.
Application of SVR with improved ant colony optimization algorithms in exchange rate forecasting
Applications comparées des méthodes d'analyse multicritère UTA
Applications de la programmation mathématique à l'analyse limite des structures
Applications of a Special Polynomial Class of Tsp
Applications of mathematical programming in graceful labeling of graphs.
Applications of nonnegative operators to a class of optimization problems
Let X be a partially ordered real Banach space, a,b ∈ X with a ≤ b. Let ϕ be a bounded linear functional on X. We call X a Ben-Israel-Charnes space (or a B-C space) if the linear program defined by Maximize ϕ(x) subject to a ≤ x ≤ b has an optimal solution for any ϕ, a and b. Such problems arise naturally in solving a class of problems known as Interval Linear Programs. B-C spaces were introduced in the author's doctoral thesis and were subsequently studied in [8] and [9]. In this article, we review...
Applications of relaxed submodularity.
Applications of the Fréchet subdifferential
2000 Mathematics Subject Classification: 46A30, 54C60, 90C26.In this paper we prove two results of nonsmooth analysis involving the Fréchet subdifferential. One of these results provides a necessary optimality condition for an optimization problem which arise naturally from a class of wide studied problems. In the second result we establish a sufficient condition for the metric regularity of a set-valued map without continuity assumptions.
Approaches to Identification of Linear Relations from Compound Noisy and Noise-Free Data
Approximate dynamic programming based on high dimensional model representation
This article introduces an algorithm for implicit High Dimensional Model Representation (HDMR) of the Bellman equation. This approximation technique reduces memory demands of the algorithm considerably. Moreover, we show that HDMR enables fast approximate minimization which is essential for evaluation of the Bellman function. In each time step, the problem of parametrized HDMR minimization is relaxed into trust region problems, all sharing the same matrix. Finding its eigenvalue decomposition, we...
Approximate Reasoning Based Optimization
Approximate solution of stochastic programming problems with recourse
Approximating the solution of a dynamic, stochastic multiple knapsack problem
Approximation algorithms for integer covering problems via greedy column generation