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Publicações

2026

Car rental fleet and demand management: An optimization framework

Autores
Oliveira, BB;

Publicação
Encyclopedia in Operations Management

Abstract
Car rental provides an essential mobility solution. The operational complexity requires efficient fleet and demand management, with significant challenges and opportunities in Operations Management. This chapter provides an overview of these issues, discussing key definitions, critical issues, recent developments, and future research directions. We focus on the car rental capacity-pricing problem under uncertainty, which integrates fleet and demand management. We explore mathematical models for this problem and discuss a co-evolutionary algorithmic framework to solve it. Current developments emphasize the need for a sustainability outlook in this business and its integration with other transportation modes. Future research should focus on advanced demand modeling, sustainable fleet management, and innovative pricing strategies, addressing the dynamic and competitive nature of the business. © 2026 Elsevier Inc. All rights are reserved, including those for text and data mining, AI training, and similar technologies.

2026

Weakly Supervised Multimodal Explanations for Medical Image Classification

Autores
Isabel Cristina Rio-Torto de Oliveira;

Publicação

Abstract

2026

Environmental and Nutritional Sustainability of Diets: Exploring Food Consumption Patterns Between Different Sustainability Groups

Autores
Bôto, JM; Miguéis, V; Rocha, A; Neto, B;

Publicação
SUSTAINABLE DEVELOPMENT

Abstract
Food sustainability is a vital global challenge, as dietary choices affect both human health and the environment. This study evaluates Portuguese dietary patterns' environmental and nutritional sustainability dimensions using data from the National Food, Nutrition, and Physical Activity Survey (IAN-AF) 2015-2016. Environmental indicators (carbon footprint, water footprint, and land use) and a nutritional quality index (NRD9.3) were analysed. Sustainability scores were calculated based on deviations from population medians, with the environmental score estimated from a weighted mean of the three indicators. A quadrant analysis classified individuals into four sustainability segments: better environmental and better nutritional scores (reference group); worse environmental and worse nutritional scores; worse environmental and better nutritional scores; and better environmental and worse nutritional scores. The reference group, with higher plant-based food consumption, had the lowest environmental impacts, 33% lower carbon footprint, 36% lower water footprint, and 50% lower land use, while exhibiting 87% better nutritional quality. In contrast, the worse environmental and worse nutritional scores group, with a diet rich in red and processed meats, sweets, and alcohol, showed higher environmental impacts and poorer nutritional quality. The group with worse environmental and better nutritional scores favored dairy and seafood, whereas the group with better environmental and worse nutritional scores had higher intakes of white meat, sweets, and alcohol. Sociodemographic factors, including sex, age, and education, show to influence the sustainability dimensions. These findings highlight the need for tailored dietary strategies that consider differing environmental and nutritional profiles, supporting more effective and practical public health interventions.

2025

Image Stitching Baseado em Bifurcações Vasculares Aplicado a Retinografias de Baixa Resolução

Autores
Guilherme G. S. Nunes; João D. S. Almeida; Darlan B. P. Quitanilha; António Cunha;

Publicação
Anais do XXV Simpósio Brasileiro de Computação Aplicada à Saúde (SBCAS 2025)

Abstract
O image stitching é uma técnica que permite combinar múltiplas imagens, formando uma imagem única com um campo de visão amplo. No contexto da retinografia, essa técnica é crucial para capturar uma visão detalhada da retina, permitindo que exames mais amplos sejam realizados. Neste trabalho, é apresentado um método de costura de imagens de baixa resolução, utilizando pontos de bifurcação como características da imagem. O método proposto apresenta um aumento das correspondências obtidas em relação aos detectores da literatura, obtendo o resultado de RMSE com uma redução de aproximadamente 14% em comparação ao SIFT (24,29) e ORB (24,32). Além disso, o método proposto obteve um PSNR médio superior, atingindo 26,27 para imagens de glaucoma, 26,72 para imagens normais e 26,71 para imagens de pacientes suspeitos, enquanto os métodos baseados em SIFT e ORB apresentaram valores inferiores, confirmando a eficácia da abordagem proposta.

2025

Decision Support System for Scheduling Vehicle Maintenance and Repair Activities in an Automotive Repair Shop

Autores
Martins, J; Ramos, AG;

Publicação
OPTIMIZATION, LEARNING ALGORITHMS AND APPLICATIONS, OL2A 2025, PT I

Abstract
To maintain high levels of efficiency and compliance with delivery dates, automotive repair shops must have a good system for scheduling their activities. The scheduling of the activities of an automotive repair shop is a very complex task to be performed manually. Throughout this work, a Decision Support System (DSS) was developed and tested that considers two major constraints in an automotive workshop: human resources (technicians) and physical resources (work stalls). The proposed DSS has an embedded MIP model that assigns a technician and a work stall to each job, according to the input conditions. The DSS also generates schedules with the planning of technicians and jobs. The system was tested with real data from an automotive workshop and was able to create plans and schedules not only for the human and physical resources in but also to analyse the limiting resources of the workshop.

2025

Towards a Framework for Service Quality Improvement in Startup Companies

Autores
Feversani, DP; de Castro, MV; Marcos, E; Teixeira, JG;

Publicação
PROCEEDINGS OF THE 58TH HAWAII INTERNATIONAL CONFERENCE ON SYSTEM SCIENCES

Abstract
Startups are vital to the economy and the digital future and are creators of around 50% of new jobs. Some studies indicate that around 90% of startups fail in their first months, mainly because they focus on launching products or services without adequate market validation. In addition, they have little or no experience in organisational management and lack the resources to apply quality models, which hinders their ability to face the challenges of a highly volatile and competitive environment. Therefore, this paper proposes the LightStartup framework, focused on startups in the service sector. LightStartup provides a lightweight, consistent and formalised process model, a process assessment model and a maturity model based on the ISO/IEC 33000 standard. LightStartup accompanies companies in transitioning from an informal management style to a formal and long-lasting management system, covering the management of services, people, customers and organisational governance.

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