Professor Rafael Martinelli, from the Department of Industrial Engineering, was interviewed by O Globo newspaper about public transportation in Rio de Janeiro. See more in the post (in Portuguese) made by CTC/PUC-Rio below.
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Two graduate students from the Department of Industrial Engineering (DEI) of the Scientific Technical Center of PUC-Rio (CTC/PUC-Rio) were awarded by the National Association of Graduate Studies and Research in Production Engineering (Anpepro). Held between September 14 and 16, the Scientific Meeting of the National Association of Graduate Studies and Research in Production Engineering (EPPGEP) awarded Raissa Zurli Bittencourt Bravo and João Marcos Dusi Vilela the awards for Best Student Publication with Technological Production and Best Academic Master’s Publication, respectively.
Raissa Bravo’s study was motivated by the occurrence of natural disasters and their effects on ecosystems and economic and social sectors. Entitled “DRAI – Monitoring and warning of droughts in Brazil: a new approach based on a risk index”, the article proposed a system for monitoring and warning droughts in the semi-arid region of Brazil, called the Drought Risk Assessment Interface (DRAI). The mechanism indicates the risk of drought in a given region based on its social and meteorological indicators. “I was very happy to receive the technological product award of EPPGEP 2022 because DRAI is a tool that, because it is web and multilingual, can be used by all those who study on the subject and who deal directly with droughts,” said Bravo. The project was guided by Profs. Fernando Cyrino and Adriana Leiras.
João Vilela’s study presents two efficient algorithms for the definition of geographic routes and long-distance power transmission lines, with more realistic paths. Entitled “Efficient algorithms for shorter-path problems adjacent quadratics”, the work seeks to contribute to the installation of a safer electrical system, so as to benefit the country’s consumers.”This award is a milestone in my academic and professional career, which I will carry with great pride throughout my life,” Vilela said. The project was guided by Profs. Bruno Fânzeres and Rafael Martinelli.
Since 2017, CTC/PUC-Rio’s Production Engineering students have won 13 honors. Being three awards for Best Publication Student with Technological Production, two for Best Publication of Academic Master’s Degree, one for Best Publication Doctoral Student, one for Best Publication Professional Master’s Student and six Special Mentions.
The EPPGEP is the annual scientific meeting of Anpepro, which brings together the coordinators of the graduate programs of the main Brazilian universities, including COPPE-UFRJ, POLI-USP, PUC-Rio, UFMG, UFPB, UFPE, UFRGS, UFSC and UFSCar.The event has the following objectives: focus on research; creation of an environment of counseling to graduate students and recognition of outstanding students. A rigorous committee, formed by professors with CNPq productivity scholarships, recognizes and rewards the best works registered at the meeting.
Author: MAURICIO FRANCA LILA
Supervisors: Fernando Luiz Cyrino Oliveira & Erick Meira de Oliveira
Date and Time: 28/04/2023, 10:30h
Link / Room: https://puc-rio.zoom.us/j/92183949231?pwd=NllydW5pTDlLNFltN0pIN2FQa1JCdz09
Committee: Fernando Luiz Cyrino Oliveira – orientador – PUC-Rio; Erick Meira de Oliveira – co-orientador -FINEP; Helio Côrtes Vieira Lopes – PUC-Rio; Reinaldo Castro Souza – PUC-Rio; Lilian Manoel de Menezes Willenbockel – UL; Lupercio França Bessegato – UFJF; Paulo Jorge Canas Rodrigues – UFBA.
Abstract:
This study presents a set of methodological proposals related to the forecast reconciliation
in the context of Hierarchical Time Series. The main objective is to present original solutions to the theme, seeking to obtain more accurate forecasts than those obtained by independent models for the different levels of the hierarchy. The studies were conducted in real data, showing the potentiality of application of the methods developed in different scenarios, where the time series are structures in a hierarchical fashion. This thesis is composed of a set of essays that explore forecast reconciliation from the perspective of a regression model, which gives foundations to optimal reconciliation. The first contribution addresses the problem of forecast reconciliation from the perspective of robust estimators. The proposal presents an original contribution applied to data from labor force surveys in Brazil, presenting a set of solutions that can drive efficient public policies. In this case, the reconciled forecasts obtained through robust estimators provided consistent gains in terms of accuracy when compared to methods that represent the state-of-the-art on forecast reconciliation in hierarchical time series. The second contribution deals with the problem of optimal reconciliation applied to energy consumption series in Brazil. We presented an alternative proposal, less sensitive to outlying forecasts at the reconciliation stage. The results obtained in this second study show considerable improvements in standard evaluation metrics with regard to the new forecasts. A third proposal seeks to offer robust covariance structures of forecasting errors, which expands the set of strategies presented in the literature. The main contribution is to incorporate robust covariance estimates into the MinT (Minimum Trace) reconciliation approach, which minimizes reconciliation errors, offering an estimator with minimum variance.
Author: LETICIA CALDAS DOS SANTOS
Advisor: Rafael Martinelli Pinto
Date and Time: 09/29/2021, 4pm
Zoom Link: https://puc-rio.zoom.us/j/95409427545?pwd=V2ptbG5tS0JwelErbDBKbVgzSEdxZz09
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Summary:
To solve the school vehicle routing problem (SBRP), exact, heuristic and metaheuristic methods can be found in the literature. However, there is still no consensus on the best approach for the different configurations that the problem can take. The objective of this work is to apply the Iterated Local Search metaheuristic for routing a real case of rural school transport (RSBRP), minimizing the total cost and respecting the specific restrictions of the problem. The algorithms will be applied to route 17,200 students registered to use rural transport in the public education network in the state of Rio de Janeiro.
Author: LETICIA CALDAS DOS SANTOS
Advisor: Rafael Martinelli Pinto
Date and Time: 09/29/2021, 4pm
Zoom Link: https://puc-rio.zoom.us/j/95409427545?pwd=V2ptbG5tS0JwelErbDBKbVgzSEdxZz09
MeetingID:
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Summary:
To solve the school vehicle routing problem (SBRP), exact, heuristic and metaheuristic methods can be found in the literature. However, there is still no consensus on the best approach for the different configurations that the problem can take. The objective of this work is to apply the Iterated Local Search metaheuristic for routing a real case of rural school transport (RSBRP), minimizing the total cost and respecting the specific restrictions of the problem. The algorithms will be applied to route 17,200 students registered to use rural transport in the public education network in the state of Rio de Janeiro.
Breno Lobato, alumnus of Production Engineering at PUC-Rio, is one of the winners of the 2020-2021 edition of the recognition program “30 Under 30 Rising Supply Chain Stars”, promoted by the Institute for Supply Management (ISM®), as one of the emerging global leaders in various disciplines and industries related to Supply Management®.
Patrícia is a student of the Interinstitutional Master’s Degree (MINTER), a partnership between DEI/PUC-Rio and UFJF.
The award-winning article proposes to obtain a ranking of generating units using the Analytic Hierarchy Process (AHP) method, based on the maintenance indicators of the Santo Antônio Hydroelectric Power Plant (SAE). The purpose of the classification generated is to provide subsidy to assist the planning of maintenance, determining the most critical turbines for the performance of preventive maintenance, in order to increase the availability of equipment, in addition to reducing the probabilities of forced shutdowns for corrective maintenance, factors impacting on the Availability Factor (FID) of the plant. The main contribution of this work is the application of AHP to classify SAE generating units, using parameters and real historical data of the plant and hydraulic turbines.
See the certificate received by Patricia at the XXIII Brazilian Congress of Automatic – CBA 2020.
The student Patrícia de Sousa Oliveira received an Honorable Mention at the CBA 2020 (Brazilian Congress of Automatics), in the Master’s category, due to her article entitled “Performance Evaluation of Generating Units Using the AHP Method”, co-authored with her advisors André Luís Marques Marcato (UFJF) and Fernando Luiz Cyrino Oliveira (DEI/PUC-Rio).
Patrícia is a student of the Interinstitutional Master’s Degree (MINTER), a partnership between DEI/PUC-Rio and UFJF.
The award-winning article proposes to obtain a ranking of generating units using the Analytic Hierarchy Process (AHP) method, based on the maintenance indicators of the Santo Antônio Hydroelectric Power Plant (SAE). The purpose of the classification generated is to provide subsidy to assist the planning of maintenance, determining the most critical turbines for the performance of preventive maintenance, in order to increase the availability of equipment, in addition to reducing the probabilities of forced shutdowns for corrective maintenance, factors impacting the Availability Factor (FID) of the plant. The main contribution of this work is the application of AHP to classify SAE generating units, using parameters and real historical data of the plant and hydraulic turbines.
See the certificate received by Patricia at the XXIII Brazilian Congress of Automatic – CBA 2020.
Award Link: http://portal.abepro.org.br/conheca-os-ganhadores-do-premio-abepro-2020/
Student Name: Marina Weil Afonso
Name of the Advisor: Fernando Luiz Cyrino Oliveira
Course: PROFESSIONAL MASTER IN LOGISTICS
ARTICLE TITLE: Simulation applied in the logistics of cargo formation of petroleum derivative for maritime shipment
ARTICLE ABSTRACT:
The present study aims to use discrete event simulation to evaluate scenarios and propose improvements in the process of cargo formation for maritime shipment of an oil derivative. Scenarios with changes in three variables were simulated in order to observe the impact on annual production: refinery storage capacity, production flow and shipment lot size. The criticality of the process is related to the production being interrupted by lack of space for storage of the product, the intermodal transport in the chain links, the road loading window and the existence of uncertainties and restrictions inherent to the operations of production, handling, storage and transportation.
An important conclusion of the study is that working with a smaller batch for maritime shipment results in higher annual production of the derivative, that is, there is a strategy that does not involve any changes in processes or infrastructure. Other factors that contributed to the increase in annual production were the addition of a tank in the refinery and the increase in production flow.
The analyses conducted in the study are important inputs for decision-making regarding the management of refinery and supply chain inventories. The simulation technique allowed to analyze several scenarios without the need to implement them, thus proving to be an effective tool with great added value to the study and practice of the organization.
Authors’ Abstracts:
Marina Weil Afonso: Graduated in Production Engineering from the Federal University of Juiz de Fora (UFJF) in 2011 and completed a Professional Master’s Degree in Logistics at the Industrial Engineering Department of PUC-Rio in 2020. He currently works with petroleum products logistics and is attending the GCLOG Program (Graduate Certificate in Logistics and Supply Chain Management) at the Massachusetts Institute of Technology (MIT).
Master’s student Tomas Gutierrez received Honorable Mention as a distinguished master’s student at the “V Meeting of Research and Graduate Studies in Production Engineering (EPPGEP 2020) of ANPEPRO, for outstanding performance in the presentation session of his article “Can Asset Allocation Limits Determine Portfolio Risk-Return Profiles in DC Pension Schemes?”, selected as one of the best of the PPGEP/DEI-PUC-Rio for participation in the V EPPGEP 2020. Tomas is supervised by Prof. David Valladão.