Penalty fuzzy function for derivative-free optimization

Penalty and Barrier methods are normally used to solve Nonlinear Optimization Problems constrained problems. The problems appear in areas such as engineering and are often characterised by the fact that involved functions (objective and constraints) are non-smooth and/or their derivatives are not know. This means that optimization methods based on derivatives cannot net used. A Java based API was implemented, including only derivative-free optimizationmethods, to solve both constrained and unconstrained problems, which includes Penalty and Barriers methods. In this work a new penalty function, based on Fuzzy Logic, is presented. This function imposes a progressive penalization to solutions that violate the constraints. This means that the function imposes a low penalization when the violation of the constraints is low and a heavy penalisation when the violation is high. The value of the penalization is not known in beforehand, it is the outcome of a fuzzy inference engine. Numerical results comparing the proposed function with two of the classic penalty/barrier functions are presented. Regarding the presented results one can conclude that the prosed penalty function besides being very robust also exhibits a very good performance.

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.

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.

Highly scalable aggregate computations in cyber-physical systems: physical environment meets communication protocols

In this paper, we focus on large-scale and dense Cyber- Physical Systems, and discuss methods that tightly integrate communication and computing with the underlying physical environment. We present Physical Dynamic Priority Dominance ((PD)2) protocol that exemplifies a key mechanism to devise low time-complexity communication protocols for large-scale networked sensor systems. We show that using this mechanism, one can compute aggregate quantities such as the maximum or minimum of sensor readings in a time-complexity that is equivalent to essentially one message exchange. We also illustrate the use of this mechanism in a more complex task of computing the interpolation of smooth as well as non-smooth sensor data in very low timecomplexity.

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.

A Java expression evaluator for nonlinear programming

Finding the optimal value for a problem is usual in many areas of knowledge where in many cases it is needed to solve Nonlinear Optimization Problems. For some of those problems it is not possible to determine the expression for its objective function and/or its constraints, they are the result of experimental procedures, might be non-smooth, among other reasons. To solve such problems it was implemented an API contained methods to solve both constrained and unconstrained problems. This API was developed to be used either locally on the computer where the application is being executed or remotely on a server. To obtain the maximum flexibility both from the programmers’ and users’ points of view, problems can be defined as a Java class (because this API was developed in Java) or as a simple text input that is sent to the API. For this last one to be possible it was also implemented on the API an expression evaluator. One of the drawbacks of this expression evaluator is that it is slower than the Java native code. In this paper it is presented a solution that combines both options: the problem can be expressed at run-time as a string of chars that are converted to Java code, compiled and loaded dynamically. To wide the target audience of the API, this new expression evaluator is also compatible with the AMPL format.

Calculation of fractional derivatives of noisy data with genetic algorithms

This paper addresses the calculation of derivatives of fractional order for non-smooth data. The noise is avoided by adopting an optimization formulation using genetic algorithms (GA). Given the flexibility of the evolutionary schemes, a hierarchical GA composed by a series of two GAs, each one with a distinct fitness function, is established.

Economic, environmental and mixed objective functions in non-linear process optimization using simulated annealing and tabu search

Screening of topologies developed by hierarchical heuristic procedures can be carried out by comparing their optimal performance. In this work we will be exploiting mono-objective process optimization using two algorithms, simulated annealing and tabu search, and four different objective functions: two of the net present value type, one of them including environmental costs and two of the global potential impact type. The hydrodealkylation of toluene to produce benzene was used as case study, considering five topologies with different complexities mainly obtained by including or not liquid recycling and heat integration. The performance of the algorithms together with the objective functions was observed, analyzed and discussed from various perspectives: average deviation of results for each algorithm, capacity for producing high purity product, screening of topologies, objective functions robustness in screening of topologies, trade-offs between economic and environmental type objective functions and variability of optimum solutions.

Which “place and non-place” do women occupy in social economy organisations?

Scientific literature has strengthened the perpetuation of inequality factors in the labour market based on gender, despite the on-going endeavour of various political bodies and legal norms against the vertical and horizontal segregation of women. National and European statistical data shows the relevance and timeless features of theories of market segmentation associated with the labour market dating back to the 70’s of the 20th century. Hence, the European Community considers as a priority in the Europe 2020 strategy, the definition of “policies to promote gender equality […] to increase labour force participation thus adding to growth and social cohesion”. If we consider that on the one hand, social economy is fairly recognised to be equated with market actors and the State for its economic and social role in tackling the current crisis, and on the other hand, that the ideals of the sector, systematised in the “Framework Law of Social Economy” (Law no. 30/2013 8th of May), particularly in article 5 proposing “the respect for the values […] of equality and non-discrimination […], justice and equity […]”, we aim to reflect on indicators that uncover a vertical and horizontal segregation in the labour market. Departing from a mixed methodological approach (extensive and intensive), subject to the topic of "Social Entrepreneurship in Portugal" in social economy organisations, we detect very high rates of employment feminisation, with a ratio of 1 man (23%) for every 3 women (77%). Women are mainly earmarked for technical and operational activities, arising from the privileged intervention areas, namely education, training, health, elderly, families, poverty, ultimately being underrepresented in statutory boards and, as such, far removed from deliberations and strategic resolutions. This is particularly visible in the existing hierarchy of functions and management practices of the responsibility of male members. Thus, it seems easily verified that the sector is travelling away from the ideals of justice and social equity, which can crystallise the "non-place" of women in the definition of a strategic direction of social economy and in the most invisible/private “place” of the organisational setting.

Investment optimization in distribution network based on fuzzy outage parameters

This paper presents a methodology that aims to increase the probability of delivering power to any load point of the electrical distribution system by identifying new investments in distribution components. The methodology is based on statistical failure and repair data of the distribution power system components and it uses fuzzy-probabilistic modelling for system component outage parameters. Fuzzy membership functions of system component outage parameters are obtained by statistical records. A mixed integer non-linear optimization technique is developed to identify adequate investments in distribution networks components that allow increasing the availability level for any customer in the distribution system at minimum cost for the system operator. To illustrate the application of the proposed methodology, the paper includes a case study that considers a real distribution network.

Decision support system with incomplete and domain incoherent information management

Many of the most common human functions such as temporal and non-monotonic reasoning have not yet been fully mapped in developed systems, even though some theoretical breakthroughs have already been accomplished. This is mainly due to the inherent computational complexity of the theoretical approaches. In the particular area of fault diagnosis in power systems however, some systems which tried to solve the problem, have been deployed using methodologies such as production rule based expert systems, neural networks, recognition of chronicles, fuzzy expert systems, etc. SPARSE (from the Portuguese acronym, which means expert system for incident analysis and restoration support) was one of the developed systems and, in the sequence of its development, came the need to cope with incomplete and/or incorrect information as well as the traditional problems for power systems fault diagnosis based on SCADA (supervisory control and data acquisition) information retrieval, namely real-time operation, huge amounts of information, etc. This paper presents an architecture for a decision support system, which can solve the presented problems, using a symbiosis of the event calculus and the default reasoning rule based system paradigms, insuring soft real-time operation with incomplete, incorrect or domain incoherent information handling ability. A prototype implementation of this system is already at work in the control centre of the Portuguese Transmission Network.

Family and non-family businesses on internal factors of entrepreneurship

Small firms are a major player in development. Thus, entrepreneurship is frequently attached to these rms and it must be present in daily management of factors such as planning and cooperation. We intend to analyze these factors, comparing familiar and non-familiar businesses. This study was conducted in a Portuguese region in the north of Portugal - Vale do Sousa . The results allow us to conclude that even with some managerial di erences it was not possible to identify distinct patterns between them. The main goal of this paper is to open research lines on important issues to distinguish familiar from non-familiar businesses.

Entrepreneurship Strategies in Family and Non-family Businesses

The goal of the present paper is to analyse the classic entrepreneurship strategies (Innovation, Risk and Proactivity) in small and medium-sized businesses. However as presented in the title, the study will go further by comparing the results of those strategies in familiar and nonfamiliar businesses. This study was carried on in construction and industry sectors, in the region of Vale do Sousa, in the north of Portugal. In order to classify businesses as familiar or non-familiar types two criterion were adopted: (1) Management Control, (2) Family Employability. On the opposite to some studies that present a larger percentage of familiar businesses in national and European entrepreneurial fabric, the criterion used leaded to a larger number of non-familiar businesses (53%). The results showed that in general SMEs in this region are not following entrepreneurship strategies. Analysing the entire sample without a separation of businesses by nature (familiar/non-familiar) only proactivity showed to be more present in the managerial decisions. There is a lack of innovation and risk culture. Comparing the groups only on proactivity tests was possible to verify some differences. It was concluded that non-familiar businesses are more proactive than familiar ones. Between those groups there are no statistical differences on the means of the variables innovation and risk. At the same time some tests were conducted to test the differences on the variable entrepreneurship. The results were similar to innovation and risk strategies: There are no significant differences on entrepreneurship between these groups of businesses.

Effect of oxidative stress upon absorption of glucose by the human placenta: in vitro studies with BeWo cells

Pregnancy is a dynamic state and the placenta is a temporary organ that, among other important functions, plays a crucial role in the transport of nutrients and metabolites between the mother and the fetus, which is essential for a successful pregnancy. Among these nutrients, glucose is considered a primary source of energy and, therefore, fundamental to insure proper fetus development. Several studies have shown that glucose uptake is dependent on several morphological and biochemical placental conditions. Oxidative stress results from the unbalance between reactive oxygen species (ROS) and antioxidants, in favor of the first. During pregnancy, ROS, and therefore oxidative stress, increase, due to increased tissue oxygenation. Moreover, the relation between ROS and some pathological conditions during pregnancy has been well established. For these reasons, it becomes essential to understand if oxidative stress can compromise the uptake of glucose by the placenta. To make this study possible, a trophoblastic cell line, the BeWo cell line, was used. Experiments regarding glucose uptake, either under normal or oxidative stress conditions, were conducted using tert-butylhydroperoxide (tBOOH) as an oxidative stress inducer, and 3H-2-deoxy-D-glucose (3H-DG) as a glucose analogue. Afterwards, studies regarding the involvement of glucose facilitative transporters (GLUT) and the phosphatidylinositol 3-kinases (PI3K) and protein kinase C (PKC) pathways were conducted, also under normal and oxidative stress conditions. A few antioxidants, endogenous and from diet, were also tested in order to study their possible reversible effect of the oxidative effect of tBOOH upon apical 3H-DG uptake. Finally, transepithelial studies gave interesting insights regarding the apical-to-basolateral transport of 3H-DG. Results showed that 3H-DG uptake, in BeWo cells, is roughly 50% GLUT-mediated and that tBOOH (100 μM; 24h) decreases apical 3H-DG uptake in BeWo cells by about 33%, by reducing both GLUT- (by 28%) and non-GLUT-mediated (by 40%) 3H-DG uptake. Uptake of 3H-DG and the effect of tBOOH upon 3H-DG uptake are not dependent on PKC and PI3K. Moreover, the effect of tBOOH is not associated with a reduction in GLUT1 mRNA levels. Resveratrol, quercetin and epigallocatechin-3-gallate, at 50 μM, reversed, by at least 45%, the effect of tBOOH upon 3H-DG uptake. Transwell studies show that the apical-to-basolateral transepithelial transport of 3H-DG is increased by tBOOH.In conclusion, our results show that tBOOH caused a marked decrease in both GLUT and non-GLUT-mediated apical uptake of 3H-DG by BeWo cells. Given the association of increased oxidative stress levels with several important pregnancy pathologies, and the important role of glucose for fetal development, the results of this study appear very interesting.