Edilson F. Arruda

University of Southampton · Department of Decision Analytics and Risk

This paper presents the Random-Key Optimizer (RKO), a versatile and efficient stochastic local search method tailored for combinatorial optimization problems. Using the random-key concept, RKO encodes solutions as vectors of random keys that are subsequently decoded into feasible solutions via problem-specific decoders. The RKO framework is able to...

The main objective of this paper is to propose a novel SEIR stochastic epidemic model. A distinguishing feature of this new model is that it allows us to consider a setup under general latency and infectious period distributions. To some extent, queuing systems with infinitely many servers and a Markov chain with time-varying transition rate compri...

This work proposes a Markov Decision Process (MDP) model for identifying windows of opportunities to perform preventive maintenance for multi-unit parallel systems subject to a varying demand. The main contribution lies in proposing: (i) a reward function that does not depend on maintenance costs, which are typically difficult to assess and classif...

This paper proposes a novel approach that makes use of continuous-time Markov chains and regret functions to find an appropriate compromise in the context of multicriteria decision analysis (MCDA). This method was an innovation in the relationship between uncertainty and decision parameters, and it allows for a much more robust sensitivity analysis...

In this study, we deal with a real-world problem on oil & gas upstream logistics, comprehending the transport of goods from ports to maritime units, through vessels called Platform Supply Vessels (PSVs). We present an integrated methodology to define the routes of these vessels and port schedules in a three-phase framework. In the first phase, we d...

This paper aims to model and understand the traffic estimation biases in European transportation infrastructure projects in the light of data from 55 projects developed between 1992 and 2012 in 17 European Union countries. Specifically, we investigate the correlation between overestimated traffic volumes and the presence of either the European Regi...

Many countries have experienced at least two waves of the COVID-19 pandemic. The second wave is far more dangerous as distinct strains appear more harmful to human health, but it stems from the complacency about the first wave. This paper introduces a parsimonious yet representative stochastic epidemic model that simulates the uncertain spread of t...

In this study, we deal with a real-world problem on oil and gas upstream logistics, comprehending the transport of goods from ports to maritime units, through vessels called Platform Supply Vessels (PSVs). We present an integrated methodology to define the routes of these vessels and port schedules in a three-phase framework. In the first phase, we...

Este trabalho apresenta um modelo de equações diferenciais e integro-diferenciais para a dinâmica da infecção pelo vírus da imunodeficiência adquirida (HIV). Tais modelos levam em conta os processos de mutação que o vírus sofre depois de adentrar o sistema imunológico. O objetivo é acompanhar a evolução da dinâmica do vírus no sistema imunológico,...

Reinfection and multiple viral strains are among the latest challenges in the current COVID-19 pandemic. In contrast, epidemic models often consider a single strain and perennial immunity. To bridge this gap, we present a new epidemic model that simultaneously considers multiple viral strains and reinfection due to waning immunity. The model is gen...

The United Kingdom has one of the poorest lung cancer survival rates in Europe. In this study, and as part of a wider programme of research to help design and evaluate a single lung cancer pathway (SCP) for Wales, existing diagnostic pathways and processes have been mapped and then modelled with a discrete event simulation for several major Welsh c...

This paper introduces a new multi-strain epidemic model with reinfection and cross-immunity to provide insights into the resurgence of the COVID-19 epidemic in an area with reportedly high seroprevalence due to a largely unmitigated outbreak: the state of Amazonas, Brazil. Although high seroprevalence could have been expected to trigger herd immuni...

This paper introduces a new multi-strain epidemic model with reinfection and cross-immunity to provide insights into the resurgence of the COVID-19 epidemic in an area with reportedly high seroprevalence due to a largely unmitigated outbreak: the state of Amazonas, Brazil. Although high seroprevalence could have been expected to trigger herd immuni...

Background: UK’s National Health Service (NHS) has one of the poorest lung cancer survival rates in Europe. To improve patient outcomes, a single cancer pathway was introduced in the NHS. In this study, a Discrete Event Simulation was developed to understand bottlenecks during lung cancer treatment. Methods: this study focused on the lung cancer d...

In this paper we propose a novel SEIR stochastic epidemic model. A distinguishing feature of this new model is that it allows us to consider a set up under general latency and infectious period distributions. To some extent, queuing systems with infinitely many servers and a Markov chain with time-varying transition rate are the very technical unde...

In this paper we propose a novel SEIR stochastic epidemic model. A distinguishing feature of this new model is that it allows us to consider a set up under general latency and infectious period distributions. To some extent, queuing systems with infinitely many servers and a Markov chain with time-varying transition rate are the very technical unde...

Purpose: Issues on timely access to diagnosis and treatment for cancer patients are still common. Many countries developed cancer care pathways to standardise and improve the outcomes of the services. Despite the existence of the cancer pathways, health services are still struggling to deliver timely cancer care. The study aims to summarise the lit...

This work introduces a novel epidemiological model that simultaneously considers multiple viral strains, reinfections due to waning immunity response over time and an optimal control formulation. This enables us to derive optimal mitigation strategies over a prescribed time horizon under a more realistic framework that does not imply perennial immu...

This work introduces a novel epidemiological model that simultaneously considers multiple viral strains, reinfections due to waning immunity response over time and an optimal control formulation. This enables us to derive optimal mitigation strategies over a prescribed time horizon under a more realistic framework that does not imply perennial immu...

The current COVID-19 pandemic is affecting different countries in different ways. The assortment of reporting techniques alongside other issues, such as underreporting and budgetary constraints, makes predicting the spread and lethality of the virus a challenging task. This work attempts to gain a better understanding of how COVID-19 will affect on...

This paper introduces a mathematical model to describe the dynamics of the spread of H1N1 flu in a human population. The model is comprised of a system of ordinary differential equations that involve susceptible, exposed, infected and recovered/immune individuals. The distinguishing feature in the proposed model with respect to other models in the...

This works presents an innovative application of Markov Decision Process (MDP) to a medium-term mining logistics planning problem considering the mine-to-client supply chain. We implemented three distinct algorithms based on state-of-the-art approaches to solve large-scale problems, and compared their results. Furthermore, we combined all three var...

This work proposes a novel framework for planning the capacity of diagnostic tests in cancer pathways that considers the aggregate demand produced by referrals from multiple cancer specialties (sites). The framework includes an analytic tool that recursively assesses the overall daily demand for each diagnostic test and considers general distributi...

The current COVID-19 pandemic is affecting different countries in different ways. The assortment of reporting techniques alongside other issues, such as underreporting and budgetary constraints, makes predicting the spread and lethality of the virus a challenging task. This work attempts to gain a better understanding of how COVID-19 will affect on...

The current COVID-19 pandemic is affecting different countries in different ways. The assortment of reporting techniques alongside other issues, such as underreporting and budgetary constraints, makes predicting the spread and lethality of the virus a challenging task. This work attempts to gain a better understanding of how COVID-19 will affect on...

Coronavirus COVID-19 spreads through the population mostly based on social contact. To gauge the potential for widespread contagion, to cope with associated uncertainty and to inform its mitigation, more accurate and robust modelling is centrally important for policy making. We provide a flexible modelling approach that increases the accuracy with...

Coronavirus COVID-19 spreads through the population mostly based on social contact. To gauge the potential for widespread contagion, to cope with associated uncertainty and to inform its mitigation, more accurate and robust modelling is centrally important for policy making. We provide a flexible modelling approach that increases the accuracy with...

Regardless of the economic activity, decommissioning decisions are often highly complex. This is due to the diversity of operational and local parameters, as well as the multitude of stakeholders involved, who generally have conflicting interests. This sets up a challenging multi-criteria decision problem on the activities to be carried out during...

This paper is motivated by decommissioning studies in the field of oil and gas, which comprise a very large number of installations and are of interest to a large number of stakeholders. Generally, the problem gives rise to complicated multi-criteria decision aid tools that rely upon the costly evaluation of multiple criteria for every piece of equ...

Running a cost-effective human blood transfusion supply chain challenges decision makers in blood services worldwide. In this paper, we develop a Markov decision process with the objective of minimising the overall costs of internal and external collections, storing, producing and disposing of blood bags, whilst explicitly considering the probabili...

The Single Health System (SUS) is the only resource that many Brazilians have to perform a surgery. For non-emergency/urgent surgeries, this demand results in a "queue" of waiting, which, in general, is significantly large. Considering this scenario, the present work proposes an activity that makes use of Mathematical Modeling to treat the problem...

Este artigo modela a variabilidade da inflação por meio de passeio aleatório paramétrico, utilizando um modelo autorregressivo integrado generalizado, condicionalmente heterocedástico. O gráfico de variância mostra o efeito de 5 (cinco) planos de estabilização no Brasil, que consistiam principalmente em controle de preços e de depósitos em bancos,...

Finding an adequate end-of-life alternative for oil and gas installations is a very complex task. Such a complexity arises from the multiplicity of decommissioning options and the diversity of conflicting criteria. Furthermore, the decision support tools in the literature require an individual evaluation of each piece of equipment. The evaluation o...

The importance of a properly management of surgical supplies in hospitals is enhanced by high costs of the materials involved. Then, this study aims to offer to the decision maker a replenishment policy which minimizes the operation's long-run average cost. As the demand for supplies comes from surgeries, demand is indirectly obtained. Next, the mo...

Established simulation methods generally require from the modeller a broad and detailed knowledge of the system under study. This paper proposes the application of Reinforcement Learning in an Agent-Based Simulation model to enable agents to define the necessary interaction rules. The model is applied to queue network systems, which are a proxy for...

Once the end of the productive life of the offshore fields is reached, the evaluation of the best decommissioning alternative becomes a challenge due to the complexity and the diversity of the installations found in the Brazilian scenario. Decision-making problems like choice are difficult to solve, most of the time, there is not a single perfect s...

Mining is an important economic activity and a highly complex industry. As such, it demands a complex supply chain to connect mines to clients, often involving railways, ports and long-distance maritime shipping. State-of-the-art optimization tools are an invaluable asset to help manage such a complex environment, which makes mining industry a very...

Cell concentrations of the potentially harmful raphidophyte Chattonella subsalsa were quantified in surface waters of Guanabara Bay, a heavily eutrophicated estuarine system in tropical Brazil, from February 2014 to January 2018. Cells were imaged and quantified in live samples by means of an automated imaging system (FlowCam®). Bloom episodes (>0....

Mining is an important economic activity and a highly complex industry. As such, it demands a complex supply chain to connect mines to clients, often involving railways, ports and long-distance maritime shipping. State-of-the-art optimization tools are an invaluable asset to help manage such a complex environment , which makes mining industry a ver...

In this work, we analyze the capacity of the human body to combat HIV. The model here treated takes into consideration four types of defense of an organism infected by HIV: susceptible defense cells, the infected immune cells, killer T cells, and the HIV specific killer T cells. This model, therefore, analyzes the interactions between the responses...

This paper proposes a stochastic shortest path approach to find an optimal sequence of tests to confirm or discard a disease, for any prescribed optimality criterion. The idea is to select the best sequence in which to apply a series of available tests, with a view at reaching a diagnosis with minimum expenditure of resources. The proposed approach...

Electromobility can be one of many solutions to the environmental challenge facing society nowadays , and the dissemination of policies towards the adoption of electric vehicles (EVs) urges the development of studies to assess their actual benefits in contrast to both conventional and other alternative technologies. This work proposes an optimizati...

This work focuses on the computation of the steady state distribution of a Markov chain, making use of an embedding algorithm. In this regard, a well-known approach dubbed time aggregation has been proposed in (Cao et al., 2002). Roughly, the idea hinges on the partition of the state space into two subsets. The linchpin in this partitioning process...

Interest in life-cycle assessment (LCA) for foodstuffs has increased over recent years. In the same period, there could also be noticed an increased focus on food losses and waste (FLW); hence the need for guidance or a method that assesses the environmental impacts of FLW when analyzing agrifood systems with the use of LCA. This study introduces a...

Objectives To determine the optimal number of adult intensive care unit beds to reduce patient's queue waiting time and to propose policy strategies. Methods Multimethodological approach: (a) quantitative time series and queueing theory were used to predict the demand and estimate intensive care unit beds in different scenarios; (b) qualitative fo...

Humanitarian organizations often rely on donations of goods to keep their operations running for a long period. However, the donation of perishable goods, such as food and medicine, is a great challenge for logistic managers of such organizations, since deteriorated items may impose a threat to the population, if used incorrectly, and a huge cost f...

Simulation is an important tool to evaluate many systems, but it often requires detailed knowledge of each specific system and a long time to generate useful results and insights. A large portion of the required time stems from the need to define operational rules and build valid models that represent them properly. To shorten this model constructi...

This paper proposes an integrated approach for the long-term planning and surgery allocation problem with downstream constraints. It is motivated by a case study in the Brazilian National Institute of Traumatology and Orthopedics, which provides elective high complexity surgeries for patients from the Brazilian public health system. We introduce an...

p>This paper proposes an integrated approach for the long-term planning and surgery allocation problem with downstream constraints. It is motivated by a case study in the Brazilian National Institute of Traumatology and Orthopedics, which provides elective high complexity surgeries for patients from the Brazilian public health system. We introduce...

p>Motivated by Markov decision processes, this paper introduces a form of embedding for Markov chains which is based on the partition of the state space into a manageable number of subsets, with the aim of enabling a decomposition algorithm for calculating long-term costs and probabilities. The decomposition enables the decision maker to derive the...

Esse artigo utiliza a abordagem de processos de decisão de Markov para analisar modelos de fila nos quais a oferta é controlada por meio de uma política gerencial. A pesquisa respalda-se no estudo de caso relativo à escolha da política ótima de envio de ônibus itinerantes de complementação às doações de sangue do principal instituto de coleta do Es...

Os mosquitos Aedes aegypti, conhecidos popularmente de mosquitos da Dengue, são os vetores de 7 tipos de doenças: os 4 sorotipos da Dengue, Chikungunya, Zika e Febre Amarela. Devido ao clima tropical favorável e recursos ambientais, o Aedes aegypti é o principal transmissor da maioria dessas doenças, tendo seu ciclo de vida dividido em dois estágio...

Critical Care is a medical specialty which addresses the life-saving and lifesustaining management of patients at risk of imminent death. The number of Intensive Care Unit (ICU) beds has an impact on patient’s prognosis. This paper aims to determine the optimal number of ICU beds to reduce patient’s waiting time. Time series was applied to predict...

The Brazilian oil and gas (O&G) sector has huge potential to grow in the next few decades. Changes made by the Petroleum Law established the Brazilian Bid Round system to offer exploratory areas and to grant exploration and production (E&P) licences, resulting in the expansion of investment in E&P. Due to Petrobras’ monopoly in the E&P sector until...

Patients with intermediate probability of coronary disease are a diagnostic challenge and it is precisely in this population where the degree of uncertainty is greater that the diagnostic tests have their greater applicability. However, according to the current definition, subjecting to tests a population with a disease probability between 10 and 9...

RESUMO Com o crescimento da produção de petróleo no Brasil houve um considerável aumento na demanda por novas embarcações, sondas e plataformas. Para que os novos projetos ocorram de acordo com o planejado, a indústria naval deve ser capaz de atender à demanda no prazo combinado. Para a construção de uma plataforma de produção de petróleo é necessá...

RESUMO O Corpo de Fuzileiros Navais é uma Força que opera em território hostil, submetendo a tropa a alto risco. Em tal situação, é fundamental o emprego da ação de choque: um trinômio composto pela mobilidade, proteção blindada e poder de fogo. Essa ação de choque é fornecida por blindados como a viatura PIRANHA. Com o crescente apoio às operações...

Resumo Considering a simple model that describes the spread of HIV in the human body, this work proposes a strategy to minimize the side effects of medication by introducing control variables that represent the evolution of the medication levels with time. The strategy corresponds to an optimization problem with respect to a prescribed performance...

This paper applies two-phase time aggregation to solve discounted Markov decision processes (MDP). This procedure , recently proposed for average cost MDPs, is extended here discounted MDPs with a view at easing the computational burden associated to finding a quality solution within a reasonable time frame. Numerical examples are presented to illu...

OBJECTIVE To estimate the required number of public beds for adults in intensive care units in the state of Rio de Janeiro to meet the existing demand and compare results with recommendations by the Brazilian Ministry of Health. METHODS The study uses a hybrid model combining time series and queuing theory to predict the demand and estimate the nu...