Search results for "algorithm"
showing 10 items of 4887 documents
Constraint qualifications and Lagrange multipliers in nondifferentiable programming problems
1994
In this paper, we present several constraint qualifications, and we show that these conditions guarantee the nonvacuity and the boundedness of the Lagrange multiplier sets for general nondifferentiable programming problems. The relationships with various constraint qualifications are investigated.
Exact and Approximate Algorithms for Two–Criteria Topological Design Problem of WAN with Budget and Delay Constraints
2004
This paper studies the problem of designing wide area networks (WAN). In the paper the two-criteria topology assignment problem with two constraints is considered. The goal is select flow routes, channel capacities and network topology in order to minimize the total average delay per packet and the leasing cost of channels subject to the budget constraint and delay constraint. The problem is NP-complete. Then, the branch and bound method is used to construct the exact algorithm. Also the approximate algorithm is presented. Some computational results are reported. Based on computational experiments, several properties of the considered problem are formulated.
The Two-Criteria Topological Design Problem in WAN with Delay Constraint: An Algorithm and Computational Results
2003
The problem is concerned with designing of wide area networks (WAN). The problem consists in selection of flow routes, channel capacities and wide area network topology in order to minimize the total average delay per packet and the leasing cost of channels subject to delay constraint. The problem is NP complete. Then, the branch and bound method is used to construct the exact algorithm. Lower bound of the criterion function is proposed. Computational results are reported. Based on computational experiments, several properties of the considered problem are formulated.
Perfiles de potencia de las lentes de contacto medidas con NIMO TR1504
2017
This study was supported by the Ministerio de Economía y Competitividad and FEDER (Grant DPI2015-71256-R) and by the Generalitat Valenciana (Grant PROMETEOII-2014-072), Spain.
Exception-Tolerant Hierarchical Knowledge Bases for Forward Model Learning
2021
This article provides an overview of the recently proposed forward model approximation framework for learning games of the general video game artificial intelligence (GVGAI) framework. In contrast to other general game-playing algorithms, the proposed agent model does not need a full description of the game but can learn the game's rules by observing game state transitions. Based on hierarchical knowledge bases, the forward model can be learned and revised during game-play, improving the accuracy of the agent's state predictions over time. This allows the application of simulation-based search algorithms and belief revision techniques to previously unknown settings. We show that the propose…
Partial Discharges analysis and parameters identification by continuous Ant Colony Optimization
2008
The technique of ant colony optimization has been employed in this paper to efficiently deal with the problem of parameters identification in partial discharge, PD, analysis. The latter is a continuous optimization problem. From the technical point of view the identification of these parameters allows the modeling of the phenomenon of Partial Discharges in dielectrics. In this way it is possible the early diagnosis of defects in Medium Voltage cable lines and components and thus it is possible to prevent possible outages and service interruptions. Analytically, the problem consists of finding the Weibull parameters of the Pulse Amplitude Distribution (PAD) distributions allowing the identif…
An evolutionary method for complex-process optimization
2010
10 páginas, 7 figuras, 7 tablas
Black box scatter search for general classes of binary optimization problems
2010
The purpose of this paper is to apply the scatter search methodology to general classes of binary problems. We focus on optimization problems for which the solutions are represented as binary vectors and that may or may not include constraints. Binary problems arise in a variety of settings, including engineering design and statistical mechanics (e.g., the spin glass problem). A distinction is made between two sets of general constraint types that are handled directly by the solver and other constraints that are addressed via penalty functions. In both cases, however, the heuristic treats the objective function evaluation as a black box. We perform computational experiments with four well-k…
Memetic Algorithms in Continuous Optimization
2012
Intuitively, a set is considered to be discrete if it is composed of isolated elements, whereas it is considered to be continuous if it is composed of infinite and contiguous elements and does not contain “holes”.
Disturbed Exploitation compact Differential Evolution for Limited Memory Optimization Problems
2011
This paper proposes a novel and unconventional Memetic Computing approach for solving continuous optimization problems characterized by memory limitations. The proposed algorithm, unlike employing an explorative evolutionary framework and a set of local search algorithms, employs multiple exploitative search within the main framework and performs a multiple step global search by means of a randomized perturbation of the virtual population corresponding to a periodical randomization of the search for the exploitative operators. The proposed Memetic Computing approach is based on a populationless (compact) evolutionary framework which, instead of processing a population of solutions, handles …