Contingent contracts

International businesses bring with them additional negotiation complexities and extra risks, thus calling for negotiation integrative solutions and additional legal protection. The recent economic crisis forced, companies, including SMEs, to look for international markets and face these additional complexities and issues. In the search for a practical and simplified solution, to serve less sophisticated companies, this paper brings insights from the negotiation literature to a specific legal issue. Specifically, I investigate the negotiation and use of contingent agreements as a tool for facilitating the negotiation process and managing risk in international deals. Looking into an international sale of goods from Portugal to Brazil, this paper proposes the structuring of two contingent contracts related to two category of products in order to demonstrate the potential benefits of some of its relevant features, specifically the creation of incentives and identification and allocation of future risks. In general, the structuring of contingent agreements is likely to provide positive results in mitigating the issues of lack of trust and dealing with the additional risks derived from international deals, therefore facilitating and improving the overall quality of the deal.

An evolutionary multi-objective optimization system for earthworks

Earthworks involve the levelling or shaping of a target area through the moving or processing of the ground surface. Most construction projects require earthworks, which are heavily dependent on mechanical equipment (e.g., excavators, trucks and compactors). Often, earthworks are the most costly and time-consuming component of infrastructure constructions (e.g., road, railway and airports) and current pressure for higher productivity and safety highlights the need to optimize earthworks, which is a nontrivial task. Most previous attempts at tackling this problem focus on single-objective optimization of partial processes or aspects of earthworks, overlooking the advantages of a multi-objective and global optimization. This work describes a novel optimization system based on an evolutionary multi-objective approach, capable of globally optimizing several objectives simultaneously and dynamically. The proposed system views an earthwork construction as a production line, where the goal is to optimize resources under two crucial criteria (costs and duration) and focus the evolutionary search (non-dominated sorting genetic algorithm-II) on compaction allocation, using linear programming to distribute the remaining equipment (e.g., excavators). Several experiments were held using real-world data from a Portuguese construction site, showing that the proposed system is quite competitive when compared with current manual earthwork equipment allocation.

Comparison of single and multi-objective evolutionary algorithms for robust link-state routing

Traffic Engineering (TE) approaches are increasingly impor- tant in network management to allow an optimized configuration and resource allocation. In link-state routing, the task of setting appropriate weights to the links is both an important and a challenging optimization task. A number of different approaches has been put forward towards this aim, including the successful use of Evolutionary Algorithms (EAs). In this context, this work addresses the evaluation of three distinct EAs, a single and two multi-objective EAs, in two tasks related to weight setting optimization towards optimal intra-domain routing, knowing the network topology and aggregated traffic demands and seeking to mini- mize network congestion. In both tasks, the optimization considers sce- narios where there is a dynamic alteration in the state of the system, in the first considering changes in the traffic demand matrices and in the latter considering the possibility of link failures. The methods will, thus, need to simultaneously optimize for both conditions, the normal and the altered one, following a preventive TE approach towards robust configurations. Since this can be formulated as a bi-objective function, the use of multi-objective EAs, such as SPEA2 and NSGA-II, came nat- urally, being those compared to a single-objective EA. The results show a remarkable behavior of NSGA-II in all proposed tasks scaling well for harder instances, and thus presenting itself as the most promising option for TE in these scenarios.

Combining data mining and evolutionary computation for multi-criteria optimization of earthworks

Earthworks tasks aim at levelling the ground surface at a target construction area and precede any kind of structural construction (e.g., road and railway construction). It is comprised of sequential tasks, such as excavation, transportation, spreading and compaction, and it is strongly based on heavy mechanical equipment and repetitive processes. Under this context, it is essential to optimize the usage of all available resources under two key criteria: the costs and duration of earthwork projects. In this paper, we present an integrated system that uses two artificial intelligence based techniques: data mining and evolutionary multi-objective optimization. The former is used to build data-driven models capable of providing realistic estimates of resource productivity, while the latter is used to optimize resource allocation considering the two main earthwork objectives (duration and cost). Experiments held using real-world data, from a construction site, have shown that the proposed system is competitive when compared with current manual earthwork design.

Modern optimization in earthwork construction

Earthworks tasks are often regarded in transportation projects as some of the most demanding processes. In fact, sequential tasks such as excavation, transportation, spreading and compaction are strongly based on heavy mechanical equipment and repetitive processes, thus becoming as economically demanding as they are time-consuming. Moreover, actual construction requirements originate higher demands for productivity and safety in earthwork constructions. Given the percentual weight of costs and duration of earthworks in infrastructure construction, the optimal usage of every resource in these tasks is paramount. Considering the characteristics of an earthwork construction, it can be looked at as a production line based on resources (mechanical equipment) and dependency relations between sequential tasks, hence being susceptible to optimization. Up to the present, the steady development of Information Technology areas, such as databases, artificial intelligence and operations research, has resulted in the emergence of several technologies with potential application bearing that purpose in mind. Among these, modern optimization methods (also known as metaheuristics), such as evolutionary computation, have the potential to find high quality optimal solutions with a reasonable use of computational resources. In this context, this work describes an optimization algorithm for earthworks equipment allocation based on a modern optimization approach, which takes advantage of the concept that an earthwork construction can be regarded as a production line.

Ergonomic analysis in a food packaging workplace

Work-related musculoskeletal disorders (WMSD) became one of the biggest health problems in the workplace and one of the main concerns of ergonomics and despite all the technical improvements manual handling is still an important risk factor for WMSD. The current study was performed with the main objective of conducting an ergonomic analysis in a workplace that consists in packaging products in a pallet, in a food distribution industry, also called picking. In this perspective, the aim of the study is to identify if the tasks performed by operators present any risk of WMSD and, if so, to suggest proposals for minimizing the associated effort. The methodologies of ergonomic risk assessment that were initially applied were the Risk Reckoner and the Manual Handling Assessment Chart (MAC). Subsequently, in order to, on the one hand, complement the analysis performed using the two methods previously mentioned, and, on the other hand, allow an assessment of two important risk factors associated with this activity (work postures and loads handling), two additional methodologies were also selected: the Revised NIOSH Lifting Equation and the Rapid Entire Body Assessment (REBA). In all the performed approaches, the tasks of palletizing at lower levels were identified as the ones that most penalize workers in what regards the risk of development of WMSD. All methodologies identified levels of risk that require an immediate or short-term ergonomic intervention, aiming at ensuring the safety and health of workers performing such activity. The implementation of measures designed to eliminate or minimize the risk may involve the allocation of significant human and material resources that is increasingly necessary to manage efficiently. Taking into account the complexity and variability of the developed tasks, it is recommended that such a decision can be preceded by a new study using more accurate risk assessment methodologies, such as those that use monitoring tools.

Changes in population and land use over time in the Ecuadorian Amazon

This paper draws upon a detailed longitudinal survey of households living on agricultural plots in the northern three provinces of the Ecuadorian Amazon, the principal region of colonization by migrants in Ecuador since the 1970s. Following the discovery of petroleum in 1967 near what has subsequently come to be the provincial capital and largest Amazonian city of Lago Agrio, oil companies built roads to lay pipelines to extract and pump oil across the Andes for export. As a result, for the past 30 years over half of both Ecuador's export earnings and government revenues have come from petroleum extracted from this region. But the roads also facilitated massive spontaneous in-migration of families from origin areas in the Ecuadorian Sierra, characterized by minifundia and rural poverty. This paper is about those migrants and their effects on the Amazonian landscape. We discuss the data collection methodology and summarize key results on settler characteristics and changes in population, land use, land ownership, technology, labor allocation, and living conditions, as well as the relationships between changes in population and changes in land use over time. The population in the study region has been growing rapidly due to both natural population growth (high fertility) and in-migration. This has led to a dramatic process of subdivision and fragmentation of plots in the 1990's, which contrasts with the consolidation of plots that has occurred in most of the mature frontier areas of the Brazilian Amazon. This fragmentation has led to important changes in land tenure and land use, deforestation, cattle raising, labor allocation, and settler welfare.

Instrumentos de políticas públicas do turismo: uma análise empírica dos municípios portugueses

Tese de Doutoramento em Ciências da Administração

Modelos de apoio às decisão na conceção e planeamento de um armazém

Programa Doutoral em Engenharia Industrial e de Sistemas.

Project management under uncertainty: a study on solution methods

Project Management involves onetime endeavors that demand for getting it right the first time. On the other hand, project scheduling, being one of the most modeled project management process stages, still faces a wide gap from theory to practice. Demanding computational models and their consequent call for simplification, divert the implementation of such models in project management tools from the actual day to day project management process. Special focus is being made to the robustness of the generated project schedules facing the omnipresence of uncertainty. An "easy" way out is to add, more or less cleverly calculated, time buffers that always result in project duration increase and correspondingly, in cost. A better approach to deal with uncertainty seems to be to explore slack that might be present in a given project schedule, a fortiori when a non-optimal schedule is used. The combination of such approach to recent advances in modeling resource allocation and scheduling techniques to cope with the increasing flexibility in resources, as can be expressed in "Flexible Resource Constraint Project Scheduling Problem" (FRCPSP) formulations, should be a promising line of research to generate more adequate project management tools. In reality, this approach has been frequently used, by project managers in an ad-hoc way.

Project scheduling and cost minimization with multiple availability constrained resources under stochastic conditions

The authors propose a mathematical model to minimize the project total cost where there are multiple resources constrained by maximum availability. They assume the resources as renewable and the activities can use any subset of resources requiring any quantity from a limited real interval. The stochastic nature is inferred by means of a stochastic work content defined per resource within an activity and following a known distribution and the total cost is the sum of the resource allocation cost with the tardiness cost or earliness bonus in case the project finishes after or before the due date, respectively. The model was computationally implemented relying upon an interchange of two global optimization metaheuristics – the electromagnetism-like mechanism and the evolutionary strategies. Two experiments were conducted testing the implementation to projects with single and multiple resources, and with or without maximum availability constraints. The set of collected results shows good behavior in general and provide a tool to further assist project manager decision making in the planning phase.

Examining mindfulness and its relation to self-differentiation and alexithymia

Published online first in 10 July 2013

Density-dependent morphological plasticity and trade-offs among vegetative traits in Eichhornia crassipes (Pontederiaceae)

Density-dependent responses are an important component of the organism life-history, and the resource allocation theory is a central concept to the life-history theory. When resource allocation varies due to environmental changes, a plant may change its morphology or physiology to cope with the new conditions, a process known as phenotypic plasticity. Our study aimed to evaluate how plant density affects Eichhornia crassipes allocation patterns. A total of 214 individuals in high and low density were collected. The density effect was observed in all plant traits examined including biomass accumulation. All traits of E. crassipes demonstrated higher values in high density conditions, except for biomass of leaves. Density exhibited a high influence on vegetative traits of E. crassipes, but did not influence allocation pattern, since a trade-off among the vegetative traits was not found. The morphological plasticity and the absence of trade-offs were discussed as strategies to overcome neighbor plants in competition situations. In high density conditions, there were clear changes in the morphology of the plants which probably allows for their survival in a highly competitive environment.

Land cover classification of Lago Grande de Curuai floodplain (Amazon, Brazil) using multi-sensor and image fusion techniques

Given the limitations of different types of remote sensing images, automated land-cover classifications of the Amazon várzea may yield poor accuracy indexes. One way to improve accuracy is through the combination of images from different sensors, by either image fusion or multi-sensor classifications. Therefore, the objective of this study was to determine which classification method is more efficient in improving land cover classification accuracies for the Amazon várzea and similar wetland environments - (a) synthetically fused optical and SAR images or (b) multi-sensor classification of paired SAR and optical images. Land cover classifications based on images from a single sensor (Landsat TM or Radarsat-2) are compared with multi-sensor and image fusion classifications. Object-based image analyses (OBIA) and the J.48 data-mining algorithm were used for automated classification, and classification accuracies were assessed using the kappa index of agreement and the recently proposed allocation and quantity disagreement measures. Overall, optical-based classifications had better accuracy than SAR-based classifications. Once both datasets were combined using the multi-sensor approach, there was a 2% decrease in allocation disagreement, as the method was able to overcome part of the limitations present in both images. Accuracy decreased when image fusion methods were used, however. We therefore concluded that the multi-sensor classification method is more appropriate for classifying land cover in the Amazon várzea.

Deteção remota na avaliação das alterações da cobertura do solo no Parque Nacional da Peneda-Gerês

Dissertação de mestrado integrado em Engenharia Civil