2021
Authors
Cruz Cunha, MM; Martinho, R; Rijo, R; Peres, E; Domingos, D; Mateus Coelho, N;
Publication
Procedia Computer Science
Abstract
2021
Authors
Davoodi, E; Babaei, E; Mohammadi Ivatloo, B; Shafie Khah, M; Catalao, JPS;
Publication
IEEE SYSTEMS JOURNAL
Abstract
In spite of the significant advance achieved in the development of optimal power flow (OPF) programs, most of the solution methods reported in the literature have considerable difficulties in dealing with different-nature objective functions simultaneously. By leveraging recent progress on the semidefinite programming (SDP) relaxations of OPF, in the present article, attention is focused on modeling a new SDP-based multiobjective OPF (MO-OPF) problem. The proposed OPF model incorporates the classical epsilon-constraint approach through a parameterization strategy to handle the multiple objective functions and produce Pareto front. This article emphasizes the extension of the SDP-based model for MO-OPF problems to generate globally nondominated Pareto optimal solutions with uniform distribution. Numerical results on IEEE 30-, 57-, 118-bus, and Indian utility 62-bus test systems with all security and operating constraints show that the proposed convex model can produce the nondominated solutions with no duality gap in polynomial time, generate efficient Pareto set, and outperform the well-known heuristic methods generally used for the solution of MO-OPF. For instance, in comparison with the obtained results of NSGA-II for the 57-bus test system, the best compromise solution obtained by SDP has 1.55% and 7.42% less fuel cost and transmission losses, respectively.
2021
Authors
OTTONI, IC; OLIVEIRA, BMPMd; BANDONI, DH; GRAÇA, APSR;
Publication
Revista de Nutrição
Abstract
2021
Authors
Carneiro, F; Miguéis, V;
Publication
Proceedings of the International Conference on Industrial Engineering and Operations Management
Abstract
Customer segmentation is increasingly needed in a context where customer interests are vital for companies to survive. This study proposes the use of the weighted RFM (Recency, Frequency, Monetary) supported by data mining techniques and the Analytic Hierarchy Process (AHP), to classify the customers according to their lifetime value (CLV). The customer segments obtained can be used to boost marketing strategies, as these segments enable to differentiate the customers. Each segment of customers is described by a set of rules based on the customers’ purchasing patterns. The methodology developed is validated by using a real case study, i.e. a food industry company, whose core business is the production of biscuits. © IEOM Society International.
2021
Authors
Santos, MGM; Carreira, JG; Gouveia, C; Madureira, G; Penedos, T; Prata, R; Lourenço, F;
Publication
IET Conference Proceedings
Abstract
Self-healing (SH) functions have been studied through pilots on E-REDES Medium Voltage (MV) network with positive results. The natural next step would be to apply the SH concept to Low Voltage (LV) networks. However, LV and MV networks have distinct characteristics (criticality, capillarity, complexity, energy distributed by km of network, technology, etc.). The economic criteria that justify SH on MV network are not applicable to LV networks. This article presents and discusses several challenges related to implement SH to LV networks and other aspects to be considered. The SH concept is discussed when applied to LV network. Also, the advantages that operational management can achieve with this concept available on daily operations. Other big challenge is the technology evolution that must occur on sensors and, most of all, actuators, to accommodate automatisms and to be remotely monitored and controlled. Also, a telecommunication solution needs to be established to support the real-time interaction between all the components. Last, but not least, the economic aspect. How and when can an extra cost be justifiable on a network that didn't felt the necessity to be automated for so many years. Should we start to consider it now? Two use-cases are proposed. © 2021 The Institution of Engineering and Technology.
2021
Authors
Camanho, AS; Varriale, L; Barbosa, F; Sobral, T;
Publication
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
Abstract
This paper investigates the relationship between students' performance and the type of school attended during upper secondary education. The performance of three different types of schools (Liceo, Technical and Professional schools) in four Italian macroregions (North West, North East, Centre, South & Islands) is investigated. A benchmarking analysis of the variability in students' performance among regions (within macroregions) for cohorts of students attending Liceo is also conducted. The data was collected at the student level from the Italian Institute for the Evaluation of Education System (INVALSI), for the academic year 2017/18. Families with higher socio-economic status may self-select into Liceo, so a direct comparison with vocational schools could lead to biased conclusions regarding the impact of school type on student performance. To overcome this limitation, we used a Propensity Score Matching approach prior to the estimation of efficiency. A pseudo-Malmquist index, based on a metafrontier and satisfying the circular property, is developed. It enables comparing the location of the best-practice frontier for each type of school and the spread in the educational efficiency of the students attending each type of school. Thus, best performance of a given school type corresponds to the combined effect of these two aspects. This study is an interesting starting point to challenge the stereotypes that persist in Italy, especially concerning general and vocational studies and geographic differences in educational achievements.
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