2020
Authors
Farkat Diogenes, JRF; Claro, J; Rodrigues, JC; Loureiro, MV;
Publication
ENERGY RESEARCH & SOCIAL SCIENCE
Abstract
Onshore wind energy (WE) has achieved a significant diffusion worldwide, in spite of the existence of multiple barriers to the large-scale implementation of wind farms. These barriers have been reported in a large number of studies, but the literature is lacking a systematized overview of their categories and locations. Based on a framework for the analysis of barriers to the penetration of renewable energy sources proposed by Painuly [363], this systematic literature review contributes to addressing this gap, identifying barriers to the large-scale implementation of onshore wind farms by category (market failures, market distortions, economic and financial, institutional, technical, social and other barriers) and location (countries around the world), and characterizing them by the level of economic development (least developed, developing, in transition, and developed) and stage of diffusion (recent or advanced) in their locations. The framework showed a high level of fit with the case of WE and allowed the identification of 31 barriers in 159 countries. The barriers were found to be mostly present in developing economies with recent diffusion, although some barriers were found to occur broadly across developed economies, regardless of the stage of diffusion. The three most frequently observed barriers were the inadequate consideration of externalities, uncertain and unsupportive governmental policies, and insufficient transmission grids.
2020
Authors
Simoes, AC; Rodrigues, JC; Neto, P;
Publication
Proceedings - 2020 IEEE International Conference on Engineering, Technology and Innovation, ICE/ITMC 2020
Abstract
Industry 4.0 is a result of technological evolution and is intended to promote technological transformations in industry at different levels. The impact in human employment has been perceived as a major threat and is a matter of concern. Some authors argue that automation will bring unimaginable changes as soon as computers get more intelligence and as machines become able to perform complex tasks more efficiently than humans. However, technological progress is also pointed out as a stimulus for human-beings to develop the competencies that differentiate them from the machines. In this context, this study aims to explore the impacts of adopting Industry 4.0 technologies on work. The results of a comprehensive literature review provide an integrated perspective to identify and understand such impacts, analysing them in four categories: evolution of employment and creation of new jobs, human-machine interaction, new competencies creation/ development, and, organizational and professional changes. © 2020 IEEE.
2020
Authors
Abreu, P; Rodrigues, JC;
Publication
Proceedings - 2020 IEEE International Conference on Engineering, Technology and Innovation, ICE/ITMC 2020
Abstract
Similar to the case of biotechnology industry, companies providing devices in the biomedicine industry face several challenges, and to stand out from competitors need to know how to get to the right customer. Potential customers (i.e., individuals and organizations) may choose to adopt or reject an innovative product and will later confirm that decision or not. Such decision is of utmost importance to the success of innovative products and, therefore, of the company that provides them. The aim of this study is to understand how perceptions formed about a biomedical product can influence its adoption intention and behavior and, hereafter, influence the decision of other potential adopters. Findings from a multiple case study provide a clear definition of the adoption process of a specific biomedical product, combining two existing theories - the Diffusion of Innovations Theory and the Technology Acceptance Model - and including the feedback created by interactions between current users of the product and potential users, to understand what influences potential adopters' decisions. © 2020 IEEE.
2020
Authors
Lopes, RL; Figueira, G; Amorim, P; Almada Lobo, B;
Publication
INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH
Abstract
There are extensive studies in the literature about the reorder point/order quantity policies for inventory management, also known as policies. Over time different algorithms have been proposed to calculate the optimal parameters given the demand characteristics and a fixed cost structure, as well as several heuristics and meta-heuristics that calculate approximations with varying accuracy. This work proposes a new meta-heuristic that evolves closed-form expressions for both policy parameters simultaneously - Cooperative Coevolutionary Genetic Programming. The implementation used for the experimental work is verified with published results from the optimal algorithm, and a well-known hybrid heuristic. The evolved expressions are compared to those algorithms, and to the expressions of previous Genetic Programming approaches available in the literature. The results outperform the previous closed-form expressions and demonstrate competitiveness against numerical methods, reaching an optimality gap of less than , while being two orders of magnitude faster. Moreover, the evolved expressions are compact, have good generalisation capabilities, and present an interesting structure resembling previous heuristics.
2020
Authors
Hora, J; Galvao, T; Camanho, A;
Publication
INTELLIGENT TRANSPORT SYSTEMS
Abstract
The synchronization of Public Transportation (PT) systems usually considers a simplified network to optimize the flows of passengers at the principal axes of the network. This work aims to identify the most relevant transfer-connections in a PT network. This goal is pursued with the development of a methodology to identify relevant transfer-connections from entry-only Automatic Fare Collection (AFC) data. The methodology has three main steps: the implementation of the Trip-Chaining-Method (TCM) to estimate the alighting stops of each AFC record, the identification of transfers, and finally, the selection of relevant transfer-connections. The adequacy of the methodology was demonstrated with its implementation to the case study of Porto. This methodology can also be applied to PT systems using entry-exit AFC data, and in that case, the TCM would not be required.
2020
Authors
Oliveira, B; Ramos, AG; De Sousa, JP;
Publication
Transportation Research Procedia
Abstract
The negative impacts of urban logistics have fostered the search for new distribution systems in inner city deliveries. In this context, interesting solutions can be developed around two-echelon distribution systems based on mobile depots (2E-MD), where loads arriving from the periphery of the city are directly transferred, at intermediate locations, from larger to smaller vehicles more suited to operate in the city centre. Four types of 2E-MD can be identified, according to the degree of mobility of larger vehicles and their accessibility to customers. In this paper, we propose a generic three-index arc-based mixed integer programming model, for a two-echelon vehicle routing problem, with synchronisation at the satellites and multi-trips at the second echelon. This generic base model is formulated for the most restrictive type of problems, where larger vehicles visit a a single transfer location and do not perform direct deliveries to customers, but it can be easily extended to address the other types of 2E-MD. The paper presents how these extensions account for the characteristics of the different types of 2E-MD. The generic model, its extensions and the impact of a set of valid inequalities are tested using problem instances adapted from the VRP literature. Results show that the proposed extensions do adequately address the specific features of the different types of 2E-MD, including multiple visits to satellites, and direct deliveries to customers. Nevertheless, the resulting models can only tackle rather small instances, even if the formulations can be strengthened by adding the valid inequalities proposed in the paper. © 2020 The Authors. Published by ELSEVIER B.V.
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