Abstract
When using direct methods to solve continuous-time nonlinear optimal control problems, regular time meshes having equidistant spacing are most frequently used. However, in some cases, these meshes cannot cope accurately with nonlinear behaviour and increasing uniformly the number of mesh nodes may lead to a more complex problem. We propose an adaptive time-mesh refinement algorithm, considering different levels of refinement and several mesh refinement criteria. Namely, we use information of the adjoint multipliers to decide where to refine further. This technique is here tested to solve two optimal control problems. One involving nonholonomic vehicles with state constraints which is characterized by having strong nonlinearities and by discontinuous controls; the other is also a nonlinear problem of a compartmental SEIR system. The proposed strategy leads to results with higher accuracy and yet with lower overall computational time, when compared to results obtained by meshes having equidistant spacing. We also apply the necessary condition of optimality in the form of the Maximum Principle of Pontryagin to characterize the solution and to validate the numerical results.

Abstract

Abstract
This chapter describes the market entry process of Portuguese small and mediumsized enterprise (SME) into the Brazilian. This chapter explores an under-researched strand in the studies of internationalization of SMEs, namely how trust and commitment leveraged the relationship orientation of the Portuguese SME in entering into the Brazilian market. Through a Case Study the chapter explores the concept of relationship orientation, trust and commitment to analyze how a Portuguese SME managed to turn around a difficult situation transforming its associates in business partners and prevented a process of desinternationalization. © 2016 by IGI Global.

Abstract
The main objective of this chapter is to define a set of strategic lines, from the public policy point of view, so that Portuguese suppliers of the auto industry can deploy a strategic alignment throughout the supply chain in order to position themselves as potential suppliers of the global sourcing strategy of their Iberian Peninsula clients. The characterization of the auto industry in Portugal and Spain is undertaken, framing the perspective of this industry and proposing the strategic guidelines for the Portuguese auto components industry to supply the Iberian market. The study supports a synergistic strategy between the Portuguese auto components industry and the Spanish automotive industry in order to increase the Portuguese incorporation in downstream activities of the supply chain. Portuguese auto components suppliers should adopt international relational strategies throughout the value chain in order to source their Original Equipment Manufacturer (OEM) clients and to reinforce their position as global suppliers. The strategy involves the consolidation of the Portuguese automotive cluster as global suppliers through specialization.

Abstract
Demand aggregators are new market players that represent a group of consumers in the electricity market. This paper proposes an aggregator model responsible for gathering residential and commercial consumers, which has the role of managing their flexible consumption in the day-ahead electricity market. A methodology to optimize the aggregator's bids is also presented. It optimizes the scheduling of the flexible loads taking simultaneously into account the consumers' preferences and temporal trajectories of forecasted outdoor temperatures and electricity prices. The proposed methodology was tested using a case study with 200 residential and commercial consumers from the Iberian market.

Abstract
Histogram-valued variables are a particular kind of variables studied in Symbolic Data Analysis where to each entity under analysis corresponds a distribution that may be represented by a histogram or by a quantile function. Linear regression models for this type of data are necessarily more complex than a simple generalization of the classical model: the parameters cannot be negative; still the linear relation between the variables must be allowed to be either direct or inverse. In this work, we propose a new linear regression model for histogram-valued variables that solves this problem, named Distribution and Symmetric Distribution Regression Model. To determine the parameters of this model, it is necessary to solve a quadratic optimization problem, subject to non-negativity constraints on the unknowns; the error measure between the predicted and observed distributions uses the Mallows distance. As in classical analysis, the model is associated with a goodness-of-fit measure whose values range between 0 and 1. Using the proposed model, applications with real and simulated data are presented.