Direct search optimization application programming interface with remote access

Search Optimization methods are needed to solve optimization problems where the objective function and/or constraints functions might be non differentiable, non convex or might not be possible to determine its analytical expressions either due to its complexity or its cost (monetary, computational, time,...). Many optimization problems in engineering and other fields have these characteristics, because functions values can result from experimental or simulation processes, can be modelled by functions with complex expressions or by noise functions and it is impossible or very difficult to calculate their derivatives. Direct Search Optimization methods only use function values and do not need any derivatives or approximations of them. In this work we present a Java API that including several methods and algorithms, that do not use derivatives, to solve constrained and unconstrained optimization problems. Traditional API access, by installing it on the developer and/or user computer, and remote API access to it, using Web Services, are also presented. Remote access to the API has the advantage of always allow the access to the latest version of the API. For users that simply want to have a tool to solve Nonlinear Optimization Problems and do not want to integrate these methods in applications, also two applications were developed. One is a standalone Java application and the other a Web-based application, both using the developed API.

Filters method in direct search optimization, new measures to admissibility

Constrained nonlinear optimization problems are usually solved using penalty or barrier methods combined with unconstrained optimization methods. Another alternative used to solve constrained nonlinear optimization problems is the lters method. Filters method, introduced by Fletcher and Ley er in 2002, have been widely used in several areas of constrained nonlinear optimization. These methods treat optimization problem as bi-objective attempts to minimize the objective function and a continuous function that aggregates the constraint violation functions. Audet and Dennis have presented the rst lters method for derivative-free nonlinear programming, based on pattern search methods. Motivated by this work we have de- veloped a new direct search method, based on simplex methods, for general constrained optimization, that combines the features of the simplex method and lters method. This work presents a new variant of these methods which combines the lters method with other direct search methods and are proposed some alternatives to aggregate the constraint violation functions.

A web-based tool to evaluate the iterative processes of direct search methods

Constrained and unconstrained Nonlinear Optimization Problems often appear in many engineering areas. In some of these cases it is not possible to use derivative based optimization methods because the objective function is not known or it is too complex or the objective function is non-smooth. In these cases derivative based methods cannot be used and Direct Search Methods might be the most suitable optimization methods. An Application Programming Interface (API) including some of these methods was implemented using Java Technology. This API can be accessed either by applications running in the same computer where it is installed or, it can be remotely accessed through a LAN or the Internet, using webservices. From the engineering point of view, the information needed from the API is the solution for the provided problem. On the other hand, from the optimization methods researchers’ point of view, not only the solution for the problem is needed. Also additional information about the iterative process is useful, such as: the number of iterations; the value of the solution at each iteration; the stopping criteria, etc. In this paper are presented the features added to the API to allow users to access to the iterative process data.

Direct-search penalty/barrier methods

In Nonlinear Optimization Penalty and Barrier Methods are normally used to solve Constrained Problems. There are several Penalty/Barrier Methods and they are used in several areas from Engineering to Economy, through Biology, Chemistry, Physics among others. In these areas it often appears Optimization Problems in which the involved functions (objective and constraints) are non-smooth and/or their derivatives are not know. In this work some Penalty/Barrier functions are tested and compared, using in the internal process, Derivative-free, namely Direct Search, methods. This work is a part of a bigger project involving the development of an Application Programming Interface, that implements several Optimization Methods, to be used in applications that need to solve constrained and/or unconstrained Nonlinear Optimization Problems. Besides the use of it in applied mathematics research it is also to be used in engineering software packages.

Derivative-free optimization and filter methods to solve nonlinear constrained problems

In real optimization problems, usually the analytical expression of the objective function is not known, nor its derivatives, or they are complex. In these cases it becomes essential to use optimization methods where the calculation of the derivatives, or the verification of their existence, is not necessary: the Direct Search Methods or Derivative-free Methods are one solution. When the problem has constraints, penalty functions are often used. Unfortunately the choice of the penalty parameters is, frequently, very difficult, because most strategies for choosing it are heuristics strategies. As an alternative to penalty function appeared the filter methods. A filter algorithm introduces a function that aggregates the constrained violations and constructs a biobjective problem. In this problem the step is accepted if it either reduces the objective function or the constrained violation. This implies that the filter methods are less parameter dependent than a penalty function. In this work, we present a new direct search method, based on simplex methods, for general constrained optimization that combines the features of the simplex method and filter methods. This method does not compute or approximate any derivatives, penalty constants or Lagrange multipliers. The basic idea of simplex filter algorithm is to construct an initial simplex and use the simplex to drive the search. We illustrate the behavior of our algorithm through some examples. The proposed methods were implemented in Java.

Derivative-free nonlinear optimization filter simplex

The filter method is a technique for solving nonlinear programming problems. The filter algorithm has two phases in each iteration. The first one reduces a measure of infeasibility, while in the second the objective function value is reduced. In real optimization problems, usually the objective function is not differentiable or its derivatives are unknown. In these cases it becomes essential to use optimization methods where the calculation of the derivatives or the verification of their existence is not necessary: direct search methods or derivative-free methods are examples of such techniques. In this work we present a new direct search method, based on simplex methods, for general constrained optimization that combines the features of simplex and filter methods. This method neither computes nor approximates derivatives, penalty constants or Lagrange multipliers.

Molecule: sistema de organização e visualização de Tags

Diversas plataformas permitem que os utilizadores rotulem recursos com tags e partilhem informação com outros utilizadores. Assim, foram desenvolvidas várias formas de visualização das tags associados aos recursos, com o intuito de facilitar aos utilizadores a pesquisa dos mesmos, assim como a visualização do tag space. De entre os vários conceitos desenvolvidos, a nuvem de tags destaca-se como a forma mais comum de visualização. Este documento apresenta um estudo efetuado sobre as suas limitações e propõe uma forma de visualização alternativa. Sugere-se também uma nova interpretação sobre como pesquisar e visualizar informação associada a tags, diferindo assim do método de pesquisa direta do termo na base de dados que atualmente é maioritariamente utilizado. Como resultado desta implementação, obteve-se uma solução viável e inovadora, o sistema Molecule, para vários dos problemas associados à tradicional nuvem de tags.

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.

RSS and LEA adaptation for indoor location using fingerprinting

Fingerprinting is an indoor location technique, based on wireless networks, where data stored during the offline phase is compared with data collected by the mobile device during the online phase. In most of the real-life scenarios, the mobile node used throughout the offline phase is different from the mobile nodes that will be used during the online phase. This means that there might be very significant differences between the Received Signal Strength values acquired by the mobile node and the ones stored in the Fingerprinting Map. As a consequence, this difference between RSS values might contribute to increase the location estimation error. One possible solution to minimize these differences is to adapt the RSS values, acquired during the online phase, before sending them to the Location Estimation Algorithm. Also the internal parameters of the Location Estimation Algorithms, for example the weights of the Weighted k-Nearest Neighbour, might need to be tuned for every type of terminal. This paper focuses both approaches, using Direct Search optimization methods to adapt the Received Signal Strength and to tune the Location Estimation Algorithm parameters. As a result it was possible to decrease the location estimation error originally obtained without any calibration procedure.

Improvement of a filters method in a derivative free optimization

Constraints nonlinear optimization problems can be solved using penalty or barrier functions. This strategy, based on solving the problems without constraints obtained from the original problem, have shown to be e ective, particularly when used with direct search methods. An alternative to solve the previous problems is the lters method. The lters method introduced by Fletcher and Ley er in 2002, , has been widely used to solve problems of the type mentioned above. These methods use a strategy di erent from the barrier or penalty functions. The previous functions de ne a new one that combine the objective function and the constraints, while the lters method treat optimization problems as a bi-objective problems that minimize the objective function and a function that aggregates the constraints. Motivated by the work of Audet and Dennis in 2004, using lters method with derivative-free algorithms, the authors developed works where other direct search meth- ods were used, combining their potential with the lters method. More recently. In a new variant of these methods was presented, where it some alternative aggregation restrictions for the construction of lters were proposed. This paper presents a variant of the lters method, more robust than the previous ones, that has been implemented with a safeguard procedure where values of the function and constraints are interlinked and not treated completely independently.

Adaptive Penalty and Barrier function based on Fuzzy Logic

Optimization methods have been used in many areas of knowledge, such as Engineering, Statistics, Chemistry, among others, to solve optimization problems. In many cases it is not possible to use derivative methods, due to the characteristics of the problem to be solved and/or its constraints, for example if the involved functions are non-smooth and/or their derivatives are not know. To solve this type of problems a Java based API has been implemented, which includes only derivative-free optimization methods, and that can be used to solve both constrained and unconstrained problems. For solving constrained problems, the classic Penalty and Barrier functions were included in the API. In this paper a new approach to Penalty and Barrier functions, based on Fuzzy Logic, is proposed. Two penalty functions, that impose a progressive penalization to solutions that violate the constraints, are discussed. The implemented functions impose a low penalization when the violation of the constraints is low and a heavy penalty when the violation is high. Numerical results, obtained using twenty-eight test problems, comparing the proposed Fuzzy Logic based functions to six of the classic Penalty and Barrier functions are presented. Considering the achieved results, it can be concluded that the proposed penalty functions besides being very robust also have a very good performance.

Virtual communities of practice: investigating motivations and constraints in the processes of knowledge creation and transfer

With accelerated market volatility, faster response times and increased globalization, business environments are going through a major transformation and firms have intensified their search for strategies which can give them competitive advantage. This requires that companies continuously innovate, to think of new ideas that can be transformed or implemented as products, processes or services, generating value for the firm. Innovative solutions and processes are usually developed by a group of people, working together. A grouping of people that share and create new knowledge can be considered as a Community of Practice (CoP). CoP’s are places which provide a sound basis for organizational learning and encourage knowledge creation and acquisition. Virtual Communities of Practice (VCoP's) can perform a central role in promoting communication and collaboration between members who are dispersed in both time and space. Nevertheless, it is known that not all CoP's and VCoP's share the same levels of performance or produce the same results. This means that there are factors that enable or constrain the process of knowledge creation. With this in mind, we developed a case study in order to identify both the motivations and the constraints that members of an organization experience when taking part in the knowledge creating processes of VCoP's. Results show that organizational culture and professional and personal development play an important role in these processes. No interviewee referred to direct financial rewards as a motivation factor for participation in VCoPs. Most identified the difficulty in aligning objectives established by the management with justification for the time spent in the VCoP. The interviewees also said that technology is not a constraint.

Qualidade de vida relacionada com o exercício em indivíduos com asma: revisão sistemática

Background: A asma condiciona o dia-a-dia do indivíduo asmático do ponto de vista clínico e emocional demonstrando-se muitas vezes como um subtractivo da qualidade de vida (QV). Alguns estudos, com particular incidência nos últimos dez anos, para além de demonstrarem os benefícios da actividade física na componente clínica da doença, têm analisado o seu efeito na QV dos asmáticos. Objectivo: Analisar os efeitos da actividade física na QV de indivíduos com asma tendo por base uma revisão da literatura actual. Métodos: Foi conduzida uma pesquisa dos randomized controlled trials (RCT) compreendidos entre Janeiro de 2000 e Agosto de 2010, bem como as citações e as referências bibliográficas de cada estudo nas principais bases de dados de ciências da saúde (Academic Search Complete, DOAJ, Elsevier – Science Direct, Highwire Press, PubMed, Scielo Global, Scirus, Scopus, SpringerLink, Taylor & Francis e Wiley Interscience) com as palavras-chave: asthma, quality of life, QoL, physical activity, exercise, breathing, training e programme em todas as combinações possíveis. Os estudos foram analisados independentemente por dois revisores quanto aos critérios de inclusão e qualidade dos estudos. Resultados: Dos 1075 estudos identificados apenas onze foram incluídos. Destes, seis apresentaram um score 5/10, três 6/10 e dois 7/10 segundo a escala PEDro. Cinco destes estudos foram realizados em crianças entre os 7 e os 15 anos e os restantes em adultos. Os programas de intervenção dividiram-se em programas de treino aeróbio e programas de exercícios respiratórios. Todos programas de treino aeróbio apresentaram melhorias na QV demonstrando uma influência positiva do treino aeróbio na asma. Principais conclusões: Há uma tendência notória do benefício dos programas de treino aeróbio na QV dos indivíduos asmáticos. Os programas de exercícios respiratórios foram poucos e heterogéneos impossibilitando uma conclusão positiva quanto à sua recomendação para a melhoria da QV nesta patologia. Há uma grande necessidade de mais RCT com rigor metodológico.

Ant colony search algorithm for the optimal power flow problem

To maintain a power system within operation limits, a level ahead planning it is necessary to apply competitive techniques to solve the optimal power flow (OPF). OPF is a non-linear and a large combinatorial problem. The Ant Colony Search (ACS) optimization algorithm is inspired by the organized natural movement of real ants and has been successfully applied to different large combinatorial optimization problems. This paper presents an implementation of Ant Colony optimization to solve the OPF in an economic dispatch context. The proposed methodology has been developed to be used for maintenance and repairing planning with 48 to 24 hours antecipation. The main advantage of this method is its low execution time that allows the use of OPF when a large set of scenarios has to be analyzed. The paper includes a case study using the IEEE 30 bus network. The results are compared with other well-known methodologies presented in the literature.

Voices in search of a reader: the polyphonic writing of António Lobo Antunes

This paper aims at analysing the writing of the Portuguese author António Lobo Antunes, considered one of the major writers in European Literature with 26 books published, by focusing on the strategies deployed in his texts of creating micro-narratives within the main frame, and conveying the elements of individual and collective memory, past and present, the self and the others, using various voices and silences. Lobo Antunes incorporates in his writing his background as a psychiatrist at a Mental Hospital in Lisbon, until 1985 (when he decided to commit exclusively to writing), his experience as a doctor in the Portuguese Colonial War battlefield, but also the daily routines of the pre and post 25th of April 1974 (Portuguese Revolution) with subtle and ironic details of the life of the middle and upper class of Lisbon‘s society: from the traumas of the war to the simple story of the janitor, or the couple who struggles to keep their marriage functional, everything serves as material to develop and interweave a complex plot, that a lot of readers find too enwrapped and difficult to follow through. Some excerpts taken from his first three novels and books of Chronicles and his later novel – Ontem não te Vi em Babilónia (2006) – will be put forward to exemplify the complexity of the writing and the main difficulties of the reader, lost in a multitude of narrators‘ voices. Recently, Lobo Antunes has commented on his work stating: What I write can be read in the darkness. This paper aims at throwing some light by unfolding some of the strategies employed to defy new borders in the process of reading.