Solving MPCC problem with the hyperbolic penalty function

The main goal of this work is to solve mathematical program with complementarity constraints (MPCC) using nonlinear programming techniques (NLP). An hyperbolic penalty function is used to solve MPCC problems by including the complementarity constraints in the penalty term. This penalty function [1] is twice continuously differentiable and combines features of both exterior and interior penalty methods. A set of AMPL problems from MacMPEC [2] are tested and a comparative study is performed.

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.

The European challenge of KMN and innovation: a skills and competence portfolio for knowledge worker in SME's

Versão editor: http://www.isegi.unl.pt/docentes/acorreia/documentos/European_Challenge_KM_Innovation_2004.pdf

Identificação de compostos que modulam a patogénese da doença de Machado-Joseph em C.elegans: autofagia como alvo terapêutico: identification of small compounds that modulate pathogenesis of Machado-Joseph disease in a C.elegans model: targeting autophagy

A doença de Machado-Joseph (DMJ) ou ataxia espinocerebelosa do tipo 3 (SCA3), conhecida por ser a mais comum das ataxias hereditárias dominantes em todo o mundo, é uma doença neurodegenerativa autossómica dominante que leva a uma grande incapacidade motora, embora sem alterar o intelecto, culminando com a morte do doente. Atualmente não existe nenhum tratamento eficaz para esta doença. A DMJ é resultado de uma alteração genética causada pela expansão de uma sequência poliglutamínica (poliQ), na região C-terminal do gene que codifica a proteína ataxina-3 (ATXN3). Os mecanismos celulares das doenças de poliglutaminas que provocam toxicidade, bem como a função da ATXN3, não são ainda totalmente conhecidos. Neste trabalho, usamos, pela sua simplicidade e potencial genético, um pequeno animal invertebrado, o nemátode C. elegans, com o objetivo de identificar fármacos eficazes para o combate contra a patogénese da DMJ, analisando simultaneamente o seu efeito na agregação da ATXN3 mutante nas células neuronais in vivo e o seu impacto no comportamento motor dos animais. Este pequeno invertebrado proporciona grandes vantagens no estudo dos efeitos tóxicos de proteínas poliQ nos neurónios, uma vez que a transparência das suas 959 células (das quais 302 são neurónios) facilita a deteção de proteínas fluorescentes in vivo. Para além disso, esta espécie tem um ciclo de vida curto, é económica e de fácil manutenção. Neste trabalho testámos no nosso modelo transgénico da DMJ com 130Qs em C.elegans dois compostos potencialmente moduladores da agregação da ATXN3 mutante e da resultante disfunção neurológica, atuando pela via da autofagia. De modo a validar a possível importância terapêutica da ativação da autofagia os compostos candidatos escolhidos foram o Litío e o análogo da Rapamicina CCI-779, testados independentemente e em combinação. A neuroproteção conferida pelo Litío e pelo CCI-779 independentemente sugere que o uso destes fármacos possa ser considerado uma boa estratégia como terapia para a DMJ, a testar em organismos evolutivamente mais próximos do humano. A manipulação da autofagia, segundo vários autores, parece ser benéfica e pode ser a chave para o desenvolvimento de novos tratamentos para várias doenças relacionadas com a agregação proteica e o envelhecimento.

MV producers and consumers agents characterization with DSM techniques

This paper consist in the establishment of a Virtual Producer/Consumer Agent (VPCA) in order to optimize the integrated management of distributed energy resources and to improve and control Demand Side Management DSM) and its aggregated loads. The paper presents the VPCA architecture and the proposed function-based organization to be used in order to coordinate the several generation technologies, the different load types and storage systems. This VPCA organization uses a frame work based on data mining techniques to characterize the costumers. The paper includes results of several experimental tests cases, using real data and taking into account electricity generation resources as well as consumption data.

A long-term risk management tool for electricity markets using swarm intelligence

This paper addresses the optimal involvement in derivatives electricity markets of a power producer to hedge against the pool price volatility. To achieve this aim, a swarm intelligence meta-heuristic optimization technique for long-term risk management tool is proposed. This tool investigates the long-term opportunities for risk hedging available for electric power producers through the use of contracts with physical (spot and forward contracts) and financial (options contracts) settlement. The producer risk preference is formulated as a utility function (U) expressing the trade-off between the expectation and the variance of the return. Variance of return and the expectation are based on a forecasted scenario interval determined by a long-term price range forecasting model. This model also makes use of particle swarm optimization (PSO) to find the best parameters allow to achieve better forecasting results. On the other hand, the price estimation depends on load forecasting. This work also presents a regressive long-term load forecast model that make use of PSO to find the best parameters as well as in price estimation. The PSO technique performance has been evaluated by comparison with a Genetic Algorithm (GA) based approach. A case study is presented and the results are discussed taking into account the real price and load historical data from mainland Spanish electricity market demonstrating the effectiveness of the methodology handling this type of problems. Finally, conclusions are dully drawn.

Lightweight user modeling – a case study

In the context of previous publications, we propose a new lightweight UM process, intended to work as a tourism recommender system in a commercial environment. The new process tackles issues like cold start, gray sheep and over specialization through a rich user model and the application of a gradual forgetting function to the collected user action history. Also, significant performance improvements were achieved regarding the previously proposed UM process.

Cooperation mechanism for team-work based multi-agent system in dynamic scheduling through meta-heuristics

This paper describes a Multi-agent Scheduling System that assumes the existence of several Machines Agents (which are decision-making entities) distributed inside the Manufacturing System that interact and cooperate with other agents in order to obtain optimal or near-optimal global performances. Agents have to manage their internal behaviors and their relationships with other agents via cooperative negotiation in accordance with business policies defined by the user manager. Some Multi Agent Systems (MAS) organizational aspects are considered. An original Cooperation Mechanism for a Team-work based Architecture is proposed to address dynamic scheduling using Meta-Heuristics.

Work in progress: representar o «outro» segundo o pensamento antropofágico casos de estudo - Hans Staden e Les Maîtres Fous

O presente artigo analisa o filme de Luis Alberto Pereira «Hans Staden» (1999), baseado no livro de Hans Staden «Duas Viagens ao Brasil» (1557), e o documentário/filme «Les Maîtres Fous» (1955) de Jean Rouch, tendo em consideração o pensamento antropofágico. Estas obras focalizam o choque cultural entre “civilizado” e “selvagem”, entre ritual canibal e ritual antropofágico, entre o «Nós» e os «Outros», encontros que permitem uma análise mais concreta à concepção de alteridade. A representação cinematográfica permite uma aproximação ao conceito antropofágico de apropriação da cultura externa, para posteriormente a reproduzir numa interpretação segundo a concepção ocidental do que figuram os rituais em questão. O Movimento Antropófago, pelo seu carácter vanguardista, concilia a matriz fundadora brasileira e ao mesmo tempo enaltece a irreverência de análise, e neste artigo serve de fundamento teórico e prático à decomposição dos exemplos. O pensamento antropófago e a sua aplicabilidade aos exemplos seleccionados permitem também aprofundar o estudo sobre o imaginário europeu enquanto recriação de relatos datados de viajantes ou colonizadores, pois a manutenção de um acervo estereotipado historicamente serve como forma de “legitimar” concepções. As duas obras focalizam a representação indígena e africana - o “selvagem” - na construção do imaginário ocidental - “civilizado” - dicotomia que nos permite desmistificar relações interculturais.

Solving a signalized traffic intersection problem with an hyperbolic penalty function

Mathematical Program with Complementarity Constraints (MPCC) finds many applications in fields such as engineering design, economic equilibrium and mathematical programming theory itself. A queueing system model resulting from a single signalized intersection regulated by pre-timed control in traffic network is considered. The model is formulated as an MPCC problem. A MATLAB implementation based on an hyperbolic penalty function is used to solve this practical problem, computing the total average waiting time of the vehicles in all queues and the green split allocation. The problem was codified in AMPL.

Motivations in volunteer work

The objective of this paper is to review and discuss the literature about volunteers’ motivations to donate their time to NGOs (Non Governmental Organisations). According to Parboteeah, Cullenb & Lim (2004) management research has not paid much attention to voluntarism, however, voluntarism is a substantial part of productive work for many societies. Wilson & Pimm (1996) show that in Great Britain about 39% of the adult population has been involved in some volunteer activity for some period of time. In the U.S.A. these values reach 50% (Wilson & Pimm, 1996). Considering the benefits that voluntarism can bring to an organisation, we understand that more attention must be devoted to this phenomenon. The more an organisation knows volunteers, the better this organisation will be able to meet the needs and expectations of these individuals. We present a literature review that illustrates and compares the different motivations associated with volunteer work. The paper includes a bibliographical databases search in specialised journals. The search used the key words “motivations” and “voluntarism” (in the heading and text body) and covered all numbers between 2000 and 2007. We identify the existence of repeated motivations (Holmberg & Söderlung, 2005; Prouteau & Wolff, 2008; Soupourmas & Ironmonger, 2001; Yavas & Riecken, 1997), which allow the establishment of a typology of volunteers’ motivations, based on four categories: altruism, social needs, self-esteem, learning and self-development. Finally we identify three main gaps in the literature that justify further research. First, research focusing on the differences between motivations related to volunteers’ "Attraction" versus "Retention" in NGO’s is nil. Second, the great majority of the studies rely on north American (USA and Canada) and Australian context, which demands for further research in European countries. Third, the majority of NGOs researched are related to sport, art or the environment, and it would be interesting to explore the relationship between motivation and NGO type. These questions may obtain interesting answers for NGO management, in particular with regard to volunteer attraction and retention.

Motivations and management factors of volunteer work in nonprofit organisations: a literature review

The objective of this paper is to review and discuss the literature about volunteers’ motivations to donate their time to NPOs and the management factors that can influence volunteer work. Firstly, the paper illustrates and compares the different types of motivation followed by a presentation of a typology that organises the volunteers’ motivations into four types: (i) altruism, (ii) belonging, (iii) ego and social recognition and (iv) development and learning. Secondly we discuss the key management factors in volunteering: recruitment, training and rewarding. Finally, we present four gaps in the literature that justify the scope for further research: (i) omission of differences between motivations related to volunteers’ "Attraction" versus "Retention"; (ii) focus of the research on the USA, UK and Australia context; (iii) absence of comparative analyses that relate motivations by NPO types and (iv) comprehension of how management factors (recruitment, training and rewarding) influence volunteers’ satisfaction and retention.

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.

Numerical optimization experiments using the hyperbolic smoothing strategy to solve MPCC

In this work we solve Mathematical Programs with Complementarity Constraints using the hyperbolic smoothing strategy. Under this approach, the complementarity condition is relaxed through the use of the hyperbolic smoothing function, involving a positive parameter that can be decreased to zero. An iterative algorithm is implemented in MATLAB language and a set of AMPL problems from MacMPEC database were tested.