Abstract

Abstract
Wind power is the source of electrical energy that has grown more over the last years, with annual rate in installed capacity around 20%. Therefore, it is important to optimize the production efficiency of wind farms. In a wind farm, the electrical energy is collected at a central substation from different wind turbines placed nearby. This paper addresses the optimal design of the cable network interconnecting the turbines to the substation aiming to minimize not only the infrastructure cost but also the cost of the energy losses in the cables. Although this problem is non-linear, different integer linear programming models are proposed considering the wind farm technical constraints. The models are applied to three real cases Portuguese wind farms. The computational results show that the proposed models are able to compute the optimal solutions for all cases.

Abstract
In the past few decades, ecological and environmental issues have dominated the forest industry worldwide, but economic aspects have been much less studied in this dynamic period. However, a sustainable and efficient forest biomass supply is critical for socio-economic development in many regions, particularly in rural areas. Nature protection efforts have contributed to reduced harvesting quotas, which have resulted in an imbalance of the environmental functions of the forests and forest management, particularly wood supply. Considering the size and distribution of forest production management units and the forest stands that compose those units, there is a clear need for improved decision-making tools that help forest managers in planning harvest sequences. The optimization of harvest scheduling should consider economic and spatial factors, which may reduce production costs by increasing the logistic efficiency. Moreover, incorporating maximum harvesting opening size constraints into planning can help preserve biodiversity. This article presents a new spatial harvest scheduling model based on the integer programming method; it was developed using real data from a forest production unit located in the northern part of the southeast region of Brazil. The goal of the proposed scheduling approach is to maximize the net present value and concentrate the harvesting locations in each period. In spite of the fact that the object of the study is plantation forest under management different to common conditions in Europe or North America, the model is flexible and can be used in management of forest in Central Europe. © 2016 Jan Kašpar et al.

Abstract
This paper considers a multi-item inventory distribution problem motivated by a practical case occurring in the logistic operations of an hospital. There, a single warehouse supplies several nursing wards. The goal is to define a weekly distribution plan of medical products that minimizes the visits to wards, while respecting inventory capacities and safety stock levels. A mathematical formulation is introduced and several improvements such as tightening constraints, valid inequalities and an extended reformulation are discussed. In order to deal with real size instances, an hybrid heuristic based on mathematical models is introduced and the improvements are discussed. A branch-and-cut algorithm using all the discussed improvements is proposed. Finally, a computational experimentation is reported to show the relevance of the model improvements and the quality of the heuristic scheme. © Springer International Publishing AG 2016.

Abstract
We consider a single item Production-Inventory-Routing problem with a single producer/supplier and multiple retailers. Inventory management constraints are considered both at the producer and at the retailers, following a vendor managed inventory approach, where the supplier monitors the inventory at retailers and decides on the replenishment policy for each retailer. We assume a constant production capacity. Based on the mathematical formulation we discuss a classical Lagrangian relaxation which allows to decompose the problem into four subproblems, and a new Lagrangian decomposition which decomposes the problem into just a production-inventory subproblem and a routing subproblem. The new decomposition is enhanced with valid inequalities. A computational study is reported to compare the bounds from the two approaches. © Springer International Publishing AG 2016.

Abstract
In sentiment analysis the polarity of a text is often assessed recurring to sentiment lexicons, which usually consist of verbs and adjectives with an associated positive or negative value. However, in short informal texts like tweets or web comments, the absence of such words does not necessarily indicates that the text lacks opinion. Tweets like "First Paris, now Brussels... What can we do?" imply opinion in spite of not using words present in sentiment lexicons, but rather due to the general sentiment or public opinion associated with terms in a specific time and domain. In order to complement general sentiment dictionaries with those domain and time specific terms, we propose a novel system for lexicon expansion that automatically extracts the more relevant and up to date terms on several different domains and then assesses their sentiment through Twitter. Experimental results on our system show an 82% accuracy on extracting domain and time specific terms and 80% on correct polarity assessment. The achieved results provide evidence that our lexicon expansion system can extract and determined the sentiment of terms for domain and time specific corpora in a fully automatic form.