Global optimization using a genetic algorithm with hierarchically structured population

This paper applies a genetic algorithm with hierarchically structured population to solve unconstrained optimization problems. The population has individuals distributed in several overlapping clusters, each one with a leader and a variable number of support individuals. The hierarchy establishes that leaders must be fitter than its supporters with the topological organization of the clusters following a tree. Computational tests evaluate different population structures, population sizes and crossover operators for better algorithm performance. A set of known benchmark test problems is solved and the results found are compared with those obtained from other methods described in the literature, namely, two genetic algorithms, a simulated annealing, a differential evolution and a particle swarm optimization. The results indicate that the method employed is capable of achieving better performance than the previous approaches in regard as the two criteria usually employed for comparisons: the number of function evaluations and rate of success. The method also has a superior performance if the number of problems solved is taken into account. (C) 2013 Elsevier B.V. All rights reserved.

A common Tabu search algorithm for the global optimization of engineering problems

A novel common Tabu algorithm for global optimizations of engineering problems is presented. The robustness and efficiency of the presented method are evaluated by using standard mathematical functions and hy solving a practical engineering problem. The numerical results show that the proposed method is (i) superior to the conventional Tabu search algorithm in robustness, and (ii) superior to the simulated annealing algorithm in efficiency. (C) 2001 Elsevier B.V. B.V. All rights reserved.

Global optimization approach for the H2-norm model reduction problem

A branch and bound algorithm is proposed to solve the H2-norm model reduction problem for continuous-time linear systems, with conditions assuring convergence to the global optimum in finite time. The lower and upper bounds used in the optimization procedure are obtained through Linear Matrix Inequalities formulations. Examples illustrate the results.

Global optimization for the ℋ∞-norm model reduction problem

A branch and bound algorithm is proposed to solve the [image omitted]-norm model reduction problem for continuous and discrete-time linear systems, with convergence to the global optimum in a finite time. The lower and upper bounds in the optimization procedure are described by linear matrix inequalities (LMI). Also proposed are two methods with which to reduce the convergence time of the branch and bound algorithm: the first one uses the Hankel singular values as a sufficient condition to stop the algorithm, providing to the method a fast convergence to the global optimum. The second one assumes that the reduced model is in the controllable or observable canonical form. The [image omitted]-norm of the error between the original model and the reduced model is considered. Examples illustrate the application of the proposed method.

Discovering promising regions to help global numerical optimization algorithms

We have developed an algorithm using a Design of Experiments technique for reduction of search-space in global optimization problems. Our approach is called Domain Optimization Algorithm. This approach can efficiently eliminate search-space regions with low probability of containing a global optimum. The Domain Optimization Algorithm approach is based on eliminating non-promising search-space regions, which are identifyed using simple models (linear) fitted to the data. Then, we run a global optimization algorithm starting its population inside the promising region. The proposed approach with this heuristic criterion of population initialization has shown relevant results for tests using hard benchmark functions.

Search schemes for random optimization algorithms that preserve the asymptotic distribution

Markovian algorithms for estimating the global maximum or minimum of real valued functions defined on some domain Omega subset of R-d are presented. Conditions on the search schemes that preserve the asymptotic distribution are derived. Global and local search schemes satisfying these conditions are analysed and shown to yield sharper confidence intervals when compared to the i.i.d. case.

Otimização global para os problemas de redução H2 de modelos e redução H2 da ordem do controlador

A branch and bound algorithm is proposed to solve the H2-norm model reduction problem and the H2-norm controller reduction problem, with conditions assuring convergence to the global optimum in finite time. The lower and upper bounds used in the optimization procedure are obtained through linear matrix inequalities formulations. Examples illustrate the results.

The cross-entropy method and its application to minimize the ripple of magnetic levitation forces of a maglev system

This paper explores firstly the potential of a new evolutionary method - the Cross-Entropy (CE) method in solving continuous inverse electromagnetic problems. For this purpose, an adaptive updating formula for the smoothing parameter, some mutation operation, and a new termination criterion are proposed. The proposed CE based metaheuristics is applied to reduce the ripple of the magnetic levitation forces of a prototype Maglev system. The numerical results have shown that the ripple of the magnetic levitation forces of the prototype system is reduced significantly after the design optimization using the proposed algorithm.

Predicting structural models for silicon clusters

This article introduces an efficient method to generate structural models for medium-sized silicon clusters. Geometrical information obtained from previous investigations of small clusters is initially sorted and then introduced into our predictor algorithm in order to generate structural models for large clusters. The method predicts geometries whose binding energies are close (95%) to the corresponding value for the ground-state with very low computational cost. These predictions can be used as a very good initial guess for any global optimization algorithm. As a test case, information from clusters up to 14 atoms was used to predict good models for silicon clusters up to 20 atoms. We believe that the new algorithm may enhance the performance of most optimization methods whenever some previous information is available. (C) 2003 Wiley Periodicals, Inc.

A new implementation of population based incremental learning method for optimizations in electromagnetics

To enhance the global search ability of population based incremental learning (PBIL) methods, it is proposed that multiple probability vectors are to be included on available PBIL algorithms. The strategy for updating those probability vectors and the negative learning and mutation operators are thus re-defined correspondingly. Moreover, to strike the best tradeoff between exploration and exploitation searches, an adaptive updating strategy for the learning rate is designed. Numerical examples are reported to demonstrate the pros and cons of the newly implemented algorithm.

New optimality conditions for nonsmooth control problems

This work considers nonsmooth optimal control problems and provides two new sufficient conditions of optimality. The first condition involves the Lagrange multipliers while the second does not. We show that under the first new condition all processes satisfying the Pontryagin Maximum Principle (called MP-processes) are optimal. Conversely, we prove that optimal control problems in which every MP-process is optimal necessarily obey our first optimality condition. The second condition is more natural, but it is only applicable to normal problems and the converse holds just for smooth problems. Nevertheless, it is proved that for the class of normal smooth optimal control problems the two conditions are equivalent. Some examples illustrating the features of these sufficient concepts are presented. © 2012 Springer Science+Business Media New York.

Extração semi-automática do eixo de rodovia em imagens de média e alta resolução usando programação dinâmica

Pós-graduação em Ciências Cartográficas - FCT

Manobras ótimas de atitude de satélites artificiais utilizando algoritmos genéticos

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Searching for larval support for majoid families (Crustacea : Brachyura) with particular reference to Inachoididae Dana, 1851

We re-evaluated the larval support for families within majoids using the Wilcoxon signed-rank test with emphasis on Inachoididae. To accomplish our objectives, we added 10 new taxa, two of which are traditionally assigned to the family of special interest, to a previous larval database for majoids, and re-appraised the larval characters used in earlier studies. Phylogenetic analysis was performed with PAUP* using the heuristic search with 50 replicates or the branch-and-bound algorithm when possible. Multi-state transformation series were considered unordered; initially characters were equally weighted followed by successive weighting, and trees were rooted at the Oregoniidae node. Ten different topological constraints were enforced for families to evaluate tree length under the assumption of monophyly for each taxonomic entity. Our results showed that the tree length of most constrained topologies was not considerably greater than that of unconstrained analysis in which most families nested as paraphyletic taxa. This may indicate that the present larval database does not provide strong support for paraphyly of the taxa in question. For Inachoididae, although the Wilcoxon signed-rank test rejected a significant difference between unconstrained and constrained cladograms, we were unable to provide a single synapomorphy for this clade. Except for the conflicting position of Leurocyclus and Stenorhynchus, the two clades correspond to the traditional taxonomic arrangement. Among inachoidids, the clade (Anasimus (Paradasygyius (Collodes + Pyromaia))) is supported, whereas for inachids, the clade (Inachus (Macropodia + Achaeus)) is one of the most supported clades within majids. As often stated, only additional characters will provide a better test for the monophyly of Inachoididae and other families within Majoidea.

Effects of postural threat on walking features of Parkinson's disease patients

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)