Browsing by Author "Lopes, Isabel Cristina"
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- An Application of Preference-Inspired Co-Evolutionary Algorithm to SectorizationPublication . Ozturk, E. Goksu; Rocha, Pedro; Sousa, Filipe; Lima, Maria Margarida; Rodrigues, Ana Maria; Soeiro Ferreira, José; Catarina Nunes, Ana; Lopes, Isabel Cristina; Oliveira, CristinaSectorization problems have significant challenges arising from the many objectives that must be optimised simultaneously. Several methods exist to deal with these many-objective optimisation problems, but each has its limitations. This paper analyses an application of Preference Inspired Co-Evolutionary Algorithms, with goal vectors (PICEA-g) to sectorization problems. The method is tested on instances of different size difficulty levels and various configurations for mutation rate and population number. The main purpose is to find the best configuration for PICEA-g to solve sectorization problems. Performancemetrics are used to evaluate these configurations regarding the solutions’ spread, convergence, and diversity in the solution space. Several test trials showed that big and medium-sized instances perform better with low mutation rates and large population sizes. The opposite is valid for the small size instances.
- An integer programming framework for sequencing cutting patterns based on interval graph completionPublication . Lopes, Isabel Cristina; Carvalho, J. M. Valerio deWe derived a framework in integer programming, based on the properties of a linear ordering of the vertices in interval graphs, that acts as an edge completion model for obtaining interval graphs. This model can be applied to problems of sequencing cutting patterns, namely the minimization of open stacks problem (MOSP). By making small modifications in the objective function and using only some of the inequalities, the MOSP model is applied to another pattern sequencing problem that aims to minimize, not only the number of stacks, but also the order spread (the minimization of the stack occupation problem), and the model is tested.
- An integer programming model for the minimum interval graph completion problemPublication . Lopes, Isabel Cristina; Carvalho, J. M. Valerio deThe minimum interval graph completion problem consists of, given a graph G = ( V, E ), finding a supergraph H = ( V, E ∪ F ) that is an interval graph, while adding the least number of edges |F| . We present an integer programming formulation for solving the minimum interval graph completion problem recurring to a characteri- zation of interval graphs that produces a linear ordering of the maximal cliques of the solution graph.
- Beneficiaries of Social Disability Pension in Small Municipalities in the Northern Region of Portugal: Application of Cluster Analysis in the Identification of Potential CausesPublication . Torres, Cristina; Vieira, Isabel; Lopes, Isabel Cristina; Monteiro, Rui; Ferreira, Carla; Bem-Haja, InêsThis study is focused on the northern region of Portugal and addresses the number of road accidents with casualties and the number of beneficiaries of the social disability pension. Municipalities with low population density are mostly located in the hinterland. The phenomenon of population aging entails the problem of people who are unable to work and become beneficiaries of the social disability pension. The hierarchical clustering method applied in this paper characterizes 46 municipalities in northern Portugal with a population of less than 20,000 inhabitants – designated small – according to economic activity, rate of road accidents with casualties and disability pensioners. These municipalities were divided into two homogeneous groups or clusters. It was possible to identify that Cluster 1 comprises the innermost municipalities featuring few road accidents with casualties, not many disability pensioners, and a small number of companies compared to Cluster 2. This study can contribute to helping local governments’ decision-making process to improve the economic activity, reduce the region’s human desertification, and improve municipal road conditions.
- Birth rate in PortugalPublication . Guerra, Maria; Pessoa, Ana; Rodrigues, Ana; Mesquita, Maria; Babo, Lurdes; Vieira, Isabel; Lopes, Isabel Cristina; Torres, CristinaThis paper presents a study on the birth rate in Portugal. The quantitative data analysis of 308 municipalities concludes that the variables “live births of mothers residing in Portugal with Portuguese and foreign nationality”, “fertility rate of the various age groups”, “live births of mothers residing in Portugal according to their level of education” and “births by gender” are strongly correlated, presenting common factors that significantly influence the birth rate.
- Consumer Default Risk Assessment in a Banking InstitutionPublication . Silva, Eliana Costa e; Lopes, Isabel Cristina; Correia, Aldina; Faria, SusanaCredit scoring is an application of financial risk forecasting to consumer lending. In this study, statistical analysis is applied to credit scoring data from a financial institution to evaluate the default risk of consumer loans. The default risk was found to be influenced by the spread, the age of the consumer, the number of credit cards owned by the consumer. A lower spread, a higher number of credit cards and a younger age of the borrower are factors that decrease the risk of default. Clients receiving the salary in the same banking institution of the loan have less chances of default than clients receiving their salary in another institution. We also found that clients in the lowest income tax echelon have more propensity to default.
- Creating homogeneous sectors: criteria and applications of sectorizationPublication . Lopes, Isabel Cristina; Lima, Maria Margarida; Ozturk, E. Goksu; Rodrigues, Ana Maria; Nunes, Ana Catarina; Oliveira, Cristina; Soeiro Ferreira, José; Rocha, PedroSectorization is the process of grouping a set of previously defined basic units (points or small areas) into a fixed number of sectors. Sectorization is also known in the literature as districting or territory design, and is usually performed to optimize one or more criteria regarding the geographic characteristics of the territory and the planning purposes of sectors. The most common criteria are equilibrium, compactness and contiguity, which can be measured in many ways. Sectorization is similar to clustering but with a different motivation. Both aggregate smaller units into groups. But, while clustering strives for inner similarity of data, sectorization aims at outer homogeneity [1]. In clustering, groups should be very different from each other, and similar points are classified in the same cluster. In sectorization, groups should be very similar to each other, and therefore very different points can be grouped in the same sector. We classify sectorization problems into four types: basic sectorization, sectorization with service centers, resectorization, and dynamic sectorization. A Decision Support System for Sectorization, D3S, is being developed to deal with these four types of problems. Multi-objective genetic algorithms were implemented in D3S using Python, and a user-friendly web interface was developed using Django. Several applications can be solved with D3S, such as political districting, sales territory design, delivery service zones, and assignment of fire stations and health services to the population.
- Depopulation of Portugal’s interiorPublication . Suavinha, Bárbara; Alves, Maria; Magalhães, Marta; Babo, Lurdes; Torres, Cristina; Vieira, Isabel; Lopes, Isabel CristinaThe depopulation of Portugal’s interior presents a crucial socio-demographic challenge, manifesting in widening disparities between major cities and inland regions. This study examines factors influencing depopulation in Portuguese municipalities, using data from PORDATA (2022). Through Linear Discriminant Analysis on twenty quantitative variables spanning education, demographics, health, and employment, municipalities are categorised by population density. The analysis reveals significant differences between groups across all variables, reinforcing the differentiation by population density. The model achieves a 71.2% correct classification rate, highlighting education and health variables as pivotal contributors to group discrimination.
- Does corruption in the public sector reduce corporate ethics? – a panel data analysisPublication . Ferreira, Fernanda A.; Castro, Conceição; Lopes, Isabel CristinaIn a globalized world, organizations no longer operate at a national level, which poses challenges for corporate ethics standards. Ethics has gained importance in this competitive business environment. In addition, enterprises face different levels of government ethics and political systems in which they operate and when they face high levels of corruption in the public sector this may lower the standard for corporate ethics. Using regression models for panel-data, the aim of this paper is to assess the effects of corruption in the public sector on corporate ethics, in a sample of 127 countries over the period of 2006–2017. The results suggest that there is a significant and negative impact of corruption in the public sector on the ethical behavior of firms. In addition, regulatory quality, corporate accountability and internet usage have significant and positive impacts on corporate ethics. This implies that fighting public corruption, promoting the development of policies that are market-friendly, strengthening the standards of auditing and reporting, and increasing the degree of digitalization of a country can improve the ethical behavior of firms.
- E-Government as a Tool in Controlling CorruptionPublication . Castro, Conceição; Lopes, Isabel CristinaCombating corruption is crucial to achieve sustainable development. With the digital revolution, the use of Information and Communications Technology by the government can promote more efficient services, diminishing the discretionary power of officials, and thus reducing corruption and promoting sustainable development. This study empirically investigates the impact of e-Government in reducing corruption on a large panel data of 175 countries, from 2003 to 2019, by estimating regression models. The results suggest that e-Government, accountability, political stability, economic wealth, and internet are significant determinants of corruption. E-Government can be a significant tool to curb corruption, although e-Government Development Index needs to exceed a threshold of 0.39 to reduce corruption. Although e-Government is a recent phenomenon, it can be regarded as an important tool for combating corruption and improving governance, enhancing transparency in public administration, since it reduces discretional power and increases the chance of exposure, eliminating some opportunities for corruption.