Defesa Doutorado [12/04/2024 – 9:00h] Prioritization and equity in decision-making models for vulnerability driven public policies

FABIOLA NEGREIROS DE OLIVEIRA

Data: 12/04/2024, 9h

Sala Zoom:  https://puc-rio.zoom.us/j/94556137486?pwd=Wk90bDdPZ01hV2V0SHRNQ1ArbFUydz09

Orientadores: Adriana Leiras | PUC-Rio & Douglas José Alem Junior |University of Edinburgh

Resumo:

Poverty, hunger and food insecurity, illiteracy and low education, poor housing conditions, and inadequate health care describe the living conditions of thousands of families worldwide. In a scenario of limited resources, a prerequisite for decision-making is to understand the vulnerabilities of the affected population so that it is possible to target and prioritize the most in-need areas/ households/people. Among the numerous prioritization criteria, equity has emerged as a key criterion often overlooked in many prioritization processes, conceptualized in terms of fairness in allocating and distributing benefits and burdens in society. This thesis proposes to incorporate prioritization and equity issues into decision-making models for orientated vulnerable populations’ public policies. We structure an approach that integrates means of measuring vulnerability as a way of prioritization (through developing prioritization indexes) and incorporating them into a decision-making model to optimize resource allocation and distribution effectively, efficiently, and especially equitably. To shed light on this problem, we study two real and complex cases applied in the endemic disease scenario and hunger food insecurity context.

Defesa Doutorado [11/04/2024 – 09:00h] Computational Techniques and Model Accuracy for Electric Power Transmission and Distribution Solo and Coordinated System-Operational Problems

NURAN CIHANGIR MARTIN

Data: 11/04/2024, 9h

Sala Zoom: https://puc-rio.zoom.us/j/94154576603?pwd=RmN4elJxRDQraWhFVFhTRzNDRVdpdz09 & Sala 950L – localizada no 9ª do Edifício Cardeal Leme.

Orientadores: Bruno Fânzeres dos Santos

Resumo:

In response to climate change, modern power systems are undergoing a decarbonisation-based transition involving vast deployment of renewable energy sources. For the success of this transition, various challenges need to be addressed in power system operations stemming from the high output variability along with limited predictability and controllability, leading to flexibility needs in power system operations. Power flow computation – and specifically, optimal power flow and unit commitment – is one of the most important computational tools for system operators to determine the state of
the power system. This computation is performed for various decisions on the grid, to dispatch the components in the network, to reconfigure them as well as price the services provided by generators and consumers on the grid. Various simplifications are made in power flow computation to tackle the computational burden of the models, which tend to be high for realistic systems. Model accuracy is increasingly causing high costs for system operations, since the real situation is deviating from the forecast leading to a need for costly actions by system operators in real-time. This thesis focuses on challenges in modern power system operations and pricing. Firstly, the thesis constructs methods and algorithms to enhance computational capability and model accuracy for AC Network-Constrained Unit Commitment and Optimal Power Flow problems through devising an improved approximation of the physical laws governing power flows. Secondly, it applies these methods and algorithms to the coordination problem between Distribution System Operators (DSOs) and Transmission System Operators (TSOs), introducing novel distributed optimisation techniques for managing congestion and voltage problems as well as addressing network information exchange aspects. Finally, the thesis proposes a new pricing mechanism endogenously addressing the non-convex operational decisions for energy and reserve scheduling for day-ahead planning, considering stochasticity of renewable energy generation. Computational and accuracy benefits are illustrated in case studies, by employing various metrics developed.

Defesa Mestrado [08/04/2024 – 9:00h] Uma abordagem de Ciência de Dados para análise do impacto do viés cognitivo de busca de risco em tomadas de decisão individuais envolvendo perdas financeiras.

LEONARDO FREITAS SAYAO

Data: 08/04/2024, 9h, formato híbrido

Sala Zoom   https://puc-rio.zoom.us/j/96735206808?pwd=RkE4WnJnZ0UyaTFLNTlsZy9JZDRSZz09#success  |  Sala 950L  

Orientadores: Fernanda Araújo Baião Amorim | PUC-Rio

Resumo: O estudo da tomada de decisões individuais tem ganhado cada vez mais importância, desde as concepções clássicas do homem econômico até os mais recentes conceitos da racionalidade limitada e dos vieses cognitivos. Ao longo do tempo, a crescente complexidade das decisões impulsionou o desenvolvimento de tecnologias como os Sistemas de Apoio à Decisão, Sistemas Informativos e Modelos Preditivos, destacando-se a integração de Inteligência Artificial e Aprendizado de Máquina para melhorar a precisão e a eficiência das escolhas. Embora esses avanços tenham proporcionado benefícios significativos, a influência dos vieses cognitivos na tomada de decisão continua sendo um desafio relevante e pouco explorado. Esses vieses podem surgir de diversas fontes, incluindo preferências individuais, influências externas e derivações cognitivas inconscientes. Apesar dos esforços da economia comportamental em identificar e modelar esses vieses, sua aplicação em contextos de decisões individuais monetárias ainda é limitada. Portanto, este trabalho propõe uma arquitetura baseada em fundamentos ontológicos para identificar e analisar vieses cognitivos em cenários de alto risco de perdas monetárias. Através da aplicação de técnicas de Ciência de Dados e ML, o objetivo é estabelecer um módulo capaz de identificar padrões de vieses cognitivos, gerando conhecimento sobre as preferências de risco dos tomadores de decisão e seus ganhos e perdas diante das sias escolhas. O viés específico explorado neste estudo é a Busca de Risco no domínio de perdas, conforme definido no Padrão Quádruplo do Kahneman. A avaliação da eficácia dessa abordagem será realizada por meio de um estudo de caso utilizando um benchmark disponível na literatura, fornecendo insights sobre a aplicabilidade e os benefícios práticos da arquitetura proposta.

Defesa Doutorado [03/04/2024 – 14:00h]  Disaster impacts on supply chains and countermeasures strategies

BRENDA DE FARIAS OLIVEIRA CARDOSO

Data: 03/04/2024, 14h

Sala Zoom: https://puc-rio.zoom.us/j/97053319470?pwd=QW0zaUxmSEFkVGhISld6dmVFVXpWQT09

Orientadores: Adriana Leiras | PUC-Rio &  Tharcisio Cotta Fontainha | UFRJ

Resumo:

The impact of disasters causes disruptions in supply chain’s (SCs) average flow and negatively affects operations’ performance. Therefore, companies need to implement effective strategies to minimise the impacts caused by these events. In this context, this thesis aims to contribute to developing prepared and responsive supply chains to deal with disaster impacts. This research is divided into three phases. First, this study brings bibliometric analyses with an overview of the main characteristics of publications on the topic through the descriptive analysis of a systematic literature review. The second phase deepens the analyses of the systematic literature review through content analysis to identify and report the significant impacts of disasters on SCs and countermeasure strategies to mitigate the adverse effects on SCs. In the second phase, we deliver a taxonomy, a research agenda, and a framework. Finally, the third phase proposes a survey to evaluate the behaviour of digitalisation and localisation in disaster contexts, considering the opinion of 62 Brazilian SC professionals. Through structural equation modelling, the results indicate that there is a negative impact of disasters on the supply chains and that digitalisation and localisation have a moderating effect on the relationship between the main constructs.