Self-adaptive combination of global tabu search and local search for nonlinear equations

Solving systems of nonlinear equations is a very important task since the problems emerge mostly through the mathematical modelling of real problems that arise naturally in many branches of engineering and in the physical sciences. The problem can be naturally reformulated as a global optimization problem. In this paper, we show that a self-adaptive combination of a metaheuristic with a classical local search method is able to converge to some difficult problems that are not solved by Newton-type methods.

Testing Nelder-Mead Based Repulsion Algorithms for Multiple Roots of Nonlinear Systems via a Two-Level Factorial Design of Experiments

This paper addresses the challenging task of computing multiple roots of a system of nonlinear equations. A repulsion algorithm that invokes the Nelder-Mead (N-M) local search method and uses a penalty-type merit function based on the error function, known as 'erf', is presented. In the N-M algorithm context, different strategies are proposed to enhance the quality of the solutions and improve the overall efficiency. The main goal of this paper is to use a two-level factorial design of experiments to analyze the statistical significance of the observed differences in selected performance criteria produced when testing different strategies in the N-M based repulsion algorithm. The main goal of this paper is to use a two-level factorial design of experiments to analyze the statistical significance of the observed differences in selected performance criteria produced when testing different strategies in the N-M based repulsion algorithm.

A genetic algorithm for the job shop scheduling with a new local search using Monte Carlo method

This paper presents a methodology for applying scheduling algorithms using Monte Carlo simulation. The methodology is based on a decision support system (DSS). The proposed methodology combines a genetic algorithm with a new local search using Monte Carlo Method. The methodology is applied to the job shop scheduling problem (JSSP). The JSSP is a difficult problem in combinatorial optimization for which extensive investigation has been devoted to the development of efficient algorithms. The methodology is tested on a set of standard instances taken from the literature and compared with others. The computation results validate the effectiveness of the proposed methodology. The DSS developed can be utilized in a common industrial or construction environment.

Local Fractional Variational Iteration Method for Local Fractional Poisson Equations in Two Independent Variables

The local fractional Poisson equations in two independent variables that appear in mathematical physics involving the local fractional derivatives are investigated in this paper. The approximate solutions with the nondifferentiable functions are obtained by using the local fractional variational iteration method.

Local Fractional Variational Iteration Method for Local Fractional Poisson Equations in Two Independent Variables

The local fractional Poisson equations in two independent variables that appear in mathematical physics involving the local fractional derivatives are investigated in this paper. The approximate solutions with the nondifferentiable functions are obtained by using the local fractional variational iteration method.

Towards an efficient and robust foot classification from pedobarographic images

O documento em anexo encontra-se na versão post-print (versão corrigida pelo editor).

Scheduling maintenance activities of electric power transmission networks using an hybrid constraint method

In this paper we present a Constraint Logic Programming (CLP) based model, and hybrid solving method for the Scheduling of Maintenance Activities in the Power Transmission Network. The model distinguishes from others not only because of its completeness but also by the way it models and solves the Electric Constraints. Specifically we present a efficient filtering algorithm for the Electrical Constraints. Furthermore, the solving method improves the pure CLP methods efficiency by integrating a type of Local Search technique with CLP. To test the approach we compare the method results with another method using a 24 bus network, which considerers 42 tasks and 24 maintenance periods.

Estudo geológico e geotécnico de taludes rochosos em S. Pedro da Afurada (Vila Nova de Gaia): contributos para a avaliação da estabilidade estrutural

Mestrado em Engenharia Geotécnica e Geoambiente

From local to global importance measures of uncertainty propagation in composite structures

The influence of uncertainties of input parameters on output response of composite structures is investigated in this paper. In particular, the effects of deviations in mechanical properties, ply angles, ply thickness and on applied loads are studied. The uncertainty propagation and the importance measure of input parameters are analysed using three different approaches: a first-order local method, a Global Sensitivity Analysis (GSA) supported by a variance-based method and an extension of local variance to estimate the global variance over the domain of inputs. Sample results are shown for a shell composite laminated structure built with different composite systems including multi-materials. The importance measures of input parameters on structural response based on numerical results are established and discussed as a function of the anisotropy of composite materials. Needs for global variance methods are discussed by comparing the results obtained from different proposed methodologies. The objective of this paper is to contribute for the use of GSA techniques together with low expensive local importance measures.

Classification of some penalty methods

Optimization problems arise in science, engineering, economy, etc. and we need to find the best solutions for each reality. The methods used to solve these problems depend on several factors, including the amount and type of accessible information, the available algorithms for solving them, and, obviously, the intrinsic characteristics of the problem. There are many kinds of optimization problems and, consequently, many kinds of methods to solve them. When the involved functions are nonlinear and their derivatives are not known or are very difficult to calculate, these methods are more rare. These kinds of functions are frequently called black box functions. To solve such problems without constraints (unconstrained optimization), we can use direct search methods. These methods do not require any derivatives or approximations of them. But when the problem has constraints (nonlinear programming problems) and, additionally, the constraint functions are black box functions, it is much more difficult to find the most appropriate method. Penalty methods can then be used. They transform the original problem into a sequence of other problems, derived from the initial, all without constraints. Then this sequence of problems (without constraints) can be solved using the methods available for unconstrained optimization. In this chapter, we present a classification of some of the existing penalty methods and describe some of their assumptions and limitations. These methods allow the solving of optimization problems with continuous, discrete, and mixing constraints, without requiring continuity, differentiability, or convexity. Thus, penalty methods can be used as the first step in the resolution of constrained problems, by means of methods that typically are used by unconstrained problems. We also discuss a new class of penalty methods for nonlinear optimization, which adjust the penalty parameter dynamically.

Proposta metodológica para avaliação preliminar de jazigos de shale gas

O potencial de um reservatório de shale gas e influenciado por um grande número de fatores, tais como a sua mineralogia e textura, o seu tipo e maturação de querogénio, a saturação de fluidos, os mecanismos de armazenamento de gás, a profundidade do reservatório e a temperatura e pressão de poros. Nesse sentido, o principal objetivo desta tese foi estabelecer uma metodologia de avaliação preliminar de potenciais jazigos de shale gas (estudo de afloramentos com base numa litoestratigrafia de alta resolução), que foi posteriormente aplicada na Formação de Vale das Fontes (Bacia Lusitânica, Portugal). Esta tese tem a particularidade de contribuir, não só para o aprofundamento da informação a nível geoquímico do local, mas também na abordagem inovadora que permitiu a caracterização petrofísica da Formação de Vale das Fontes. Para a aplicação da metodologia estabelecida, foi necessária a realização dos seguintes ensaios laboratoriais: Rock-Eval 6, picnometria de gás hélio, ensaio de resistência a compressão simples, Darcypress e a difracção de raios-X, aplicando o método de Rietveld. Os resultados obtidos na análise petrofísica mostram uma formação rochosa de baixa porosidade que segundo a classificação ISRM, e classificada como ”Resistente”, para alem de revelar comportamento dúctil e elevado índice de fragilidade. A permeabilidade média obtida situa a Formação no intervalo correspondente as permeabilidades atribuídas aos jazigos de tigh gas, indicando a necessidade de fracturação hidráulica, no caso de uma eventual exploração de hidrocarbonetos, enquanto a difracção de raios-X destaca a calcite, o quartzo e os filossilicatos como os minerais mais presentes na Formação. Do ponto de vista geoquímico, os resultados obtidos mostram que apesar do considerável teor médio de carbono orgânico total, a natureza da matéria orgânica analisada e maioritariamente imatura, composta, principalmente, por querogénio do tipo IV, o que indica a incapacidade de a formação gerar hidrocarbonetos em quantidades economicamente exploráveis.

Territorial innovation, social ventures and local development: An exploratory case study

Social innovation is recognized as an important driver of growth and social value creation. Social innovative strategies are often pursued at the local level, by (social) organizations which have a more comprehensive knowledge of the complex social problems that a specific community is facing. The objective of the present study is to analyse the extent to which innovative social ventures are able to contribute to local development. By means of a qualitative approach, based on the case study method, we attempt to illustrate the innovative strategies conceived on the ground by a social venture specifically created to foster the local development of its inhabitants. The results shows that social innovation is a viable strategy to revitalize the economic growth of a region, through the creation of local employment on the basis of village’s traditional activities that are redefined in a new and competitive way. However, to be successful the strategy demands the deep knowledge of existing social problems as well as the availability of endogenous local resources and capabilities that could be used by social entrepreneurs. Therefore, social innovation ensures that local development and social cohesion are achieved in a sustainable way, at the same time that cultural and environmental heritage are also preserved.