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État de l'art des méthodes “d'optimisation globale”

Gérard Berthiau, Patrick Siarry (2010)

RAIRO - Operations Research

We present a review of the main “global optimization" methods. The paper comprises one introduction and two parts. In the introduction, we recall some generalities about non linear constraint-less optimization and we list some classifications which have been proposed for the global optimization methods. We then describe, in the first part, various “classical" global optimization methods, most of which available long before the appearance of Simulated Annealing (a key event in this field)....

Evaluating the Kernighan-Lin heuristic for hardware/software partitioning

Zoltán Mann, András Orbán, Viktor Farkas (2007)

International Journal of Applied Mathematics and Computer Science

In recent years, several heuristics have been proposed for the hardware/software partitioning problem. One of the most promising directions is the adaptation of the Kernighan-Lin algorithm. The Kernighan-Lin heuristic was originally developed for circuit partitioning, but it has been adapted to other domains as well. Moreover, numerous improvements have been suggested so that now several variants of the original algorithm exist. The aim of this paper is to systematically evaluate the possibilities...

Evolutionary algorithms and fuzzy sets for discovering temporal rules

Stephen G. Matthews, Mario A. Gongora, Adrian A. Hopgood (2013)

International Journal of Applied Mathematics and Computer Science

A novel method is presented for mining fuzzy association rules that have a temporal pattern. Our proposed method contributes towards discovering temporal patterns that could otherwise be lost from defining the membership functions before the mining process. The novelty of this research lies in exploring the composition of fuzzy and temporal association rules, and using a multi-objective evolutionary algorithm combined with iterative rule learning to mine many rules. Temporal patterns are augmented...

Evolutionary computation based on Bayesian classifiers

Teresa Miquélez, Endika Bengoetxea, Pedro Larrañaga (2004)

International Journal of Applied Mathematics and Computer Science

Evolutionary computation is a discipline that has been emerging for at least 40 or 50 years. All methods within this discipline are characterized by maintaining a set of possible solutions (individuals) to make them successively evolve to fitter solutions generation after generation. Examples of evolutionary computation paradigms are the broadly known Genetic Algorithms (GAs) and Estimation of Distribution Algorithms (EDAs). This paper contributes to the further development of this discipline by...

Evolutionary learning of rich neural networks in the Bayesian model selection framework

Matteo Matteucci, Dario Spadoni (2004)

International Journal of Applied Mathematics and Computer Science

In this paper we focus on the problem of using a genetic algorithm for model selection within a Bayesian framework. We propose to reduce the model selection problem to a search problem solved using evolutionary computation to explore a posterior distribution over the model space. As a case study, we introduce ELeaRNT (Evolutionary Learning of Rich Neural Network Topologies), a genetic algorithm which evolves a particular class of models, namely, Rich Neural Networks (RNN), in order to find an optimal...

Evolutionary optimization of interval mathematics-based design of a TSK fuzzy controller for anti-sway crane control

Jarosław Smoczek (2013)

International Journal of Applied Mathematics and Computer Science

A hybrid method combining an evolutionary search strategy, interval mathematics and pole assignment-based closed-loop control synthesis is proposed to design a robust TSK fuzzy controller. The design objective is to minimize the number of linear controllers associated with rule conclusions and tune the triangular-shaped membership function parameters of a fuzzy controller to satisfy stability and desired dynamic performances in the presence of system parameter variation. The robust performance objective...

Fast approximation of minimum multicast congestion – Implementation versus theory

Andreas Baltz, Anand Srivastav (2004)

RAIRO - Operations Research - Recherche Opérationnelle

The problem of minimizing the maximum edge congestion in a multicast communication network generalizes the well-known N P -hard multicommodity flow problem. We give the presently best theoretical approximation results as well as efficient implementations. In particular we show that for a network with m edges and k multicast requests, an r ( 1 + ε ) ( r t e x t O P T + exp ( 1 ) ln m ) -approximation can be computed in O ( k m ε - 2 ln k ln m ) time, where β bounds the time for computing an r -approximate minimum Steiner tree. Moreover, we present a new fast heuristic that...

Fast approximation of minimum multicast congestion – Implementation VERSUS Theory

Andreas Baltz, Anand Srivastav (2010)

RAIRO - Operations Research

The problem of minimizing the maximum edge congestion in a multicast communication network generalizes the well-known NP-hard multicommodity flow problem. We give the presently best theoretical approximation results as well as efficient implementations. In particular we show that for a network with m edges and k multicast requests, an r(1 + ε)(rOPT + exp(1)lnm)-approximation can be computed in O(kmε-2lnklnm) time, where β bounds the time for computing an r-approximate minimum Steiner tree. Moreover,...

Flots entiers et multiflots fractionnaires couplés par une contrainte de capacité

Alain Quilliot, Fatiha Bendali, Jean Mailfert (2005)

RAIRO - Operations Research - Recherche Opérationnelle

Nous modélisons ici plusieurs problèmes de Transport et de Gestion de Flux à l’aide d’un flot entier et d’un multiflot fractionnaire couplés par une contrainte de capacité. Pour le problème ainsi obtenu, nous proposons différents schémas de résolution par relaxation et décomposition, qui induisent la recherche d’un flot auxiliaire dont la partie entière supérieure doit minimiser un certain coût, et qui requièrent la mise en œuvre d’un processus d’agrégation. Nous en déduisons diverses heuristiques...

Flots entiers et multiflots fractionnaires couplés par une contrainte de capacité

Alain Quilliot, Fatiha Bendali, Jean Mailfert (2006)

RAIRO - Operations Research

Nous modélisons ici plusieurs problèmes de Transport et de Gestion de Flux à l'aide d'un flot entier et d'un multiflot fractionnaire couplés par une contrainte de capacité. Pour le problème ainsi obtenu, nous proposons différents schémas de résolution par relaxation et décomposition, qui induisent la recherche d'un flot auxiliaire dont la partie entière supérieure doit minimiser un certain coût, et qui requièrent la mise en œuvre d'un processus d'agrégation. Nous en déduisons diverses heuristiques...

France Telecom workforce scheduling problem: a challenge

Sebastian Pokutta, Gautier Stauffer (2009)

RAIRO - Operations Research

In this paper, we describe the methodology used to tackle France Telecom workforce scheduling problem (the subject of the Roadef Challenge 2007) and we report the results obtained on the different data sets provided for the competition. Since the problem at hand appears to be NP-hard and due to the high dimensions of the instance sets, we use a two-step heuristical approach. We first devise a problem-tailored heuristic that provides good feasible solutions and then we use a meta-heuristic scheme...

Fuzzy linear programming via simulated annealing

Rita Almeida Ribeiro, Fernando Moura Pires (1999)

Kybernetika

This paper shows how the simulated annealing (SA) algorithm provides a simple tool for solving fuzzy optimization problems. Often, the issue is not so much how to fuzzify or remove the conceptual imprecision, but which tools enable simple solutions for these intrinsically uncertain problems. A well-known linear programming example is used to discuss the suitability of the SA algorithm for solving fuzzy optimization problems.

Genetic algorithm based method of elimination of residual oscillation in mechatronic systems

Peter Hubinský, Ladislav Jurišica, Branislav Vranka (2005)

Kybernetika

The paper presents control signals generation methods, preventing the excitation of residual vibration in slightly damped oscillational systems. It is focused on the feedforward methods, as most of the vibrations in examined processes are induced by the control, while the influence of disturbances is mostly negligible. Application of these methods involves ensuring of the insensitivity to natural frequency change, which can be reached in classical approach only by considerable increase of transient...

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