Hybrid Approaches of Verbal Decision Analysis in the Selection of Project Management Approaches

AbstractDecision support methods aim at assisting in the decision-making process by simplifying the analysis of the problem and justifying the choice of a particular potential action. Recent researches have shown that the hybridization of methods is able to overcome limitations presented by the methods when applied separately: the classification of alternatives before submitting them to an ordination methodology would be an e ective way of filtering the set to be ordered. Specific Practices of Capability Maturity Model Integration were analyzed through a decision making model, assisted by the methods SAC and ZAPROS III-i. The results will be compared to previous studies

Handling Diagnosis of Schizophrenia by a Hybrid Method

Psychotics disorders, most commonly known as schizophrenia, have incapacitated professionals in different sectors of activities. Those disorders have caused damage in a microlevel to the individual and his/her family and in a macrolevel to the economic and production system of the country. The lack of early and sometimes very late diagnosis has provided reactive measures, when the professional is already showing psychological signs of incapacity to work. This study aims to help the early diagnosis of psychotics’ disorders with a hybrid proposal of an expert system that is integrated to structured methodologies in decision support (multicriteria decision analysis: MCDA) and knowledge structured representations into production rules and probabilities (artificial intelligence: AI)

Dealing with Nonregular Shapes Packing

This paper addresses the irregular strip packing problem, a particular two-dimensional cutting and packing problem in which convex/nonconvex shapes (polygons) have to be packed onto a single rectangular object. We propose an approach that prescribes the integration of a metaheuristic engine (i.e., genetic algorithm) and a placement rule (i.e., greedy bottom-left). Moreover, a shrinking algorithm is encapsulated into the metaheuristic engine to improve good quality solutions. To accomplish this task, we propose a no-fit polygon based heuristic that shifts polygons closer to each other. Computational experiments performed on standard benchmark problems, as well as practical case studies developed in the ambit of a large textile industry, are also reported and discussed here in order to testify the potentialities of proposed approach

Hybrid model for early identification post-Covid-19 sequelae

Artificial Intelligence techniques based on Machine Learning algorithms, Neural Networks and Naïve Bayes can optimise the diagnostic process of the SARS-CoV-2 or Covid-19. The most significant help of these techniques is analysing data recorded by health professionals when treating patients with this disease. Health professionals' more specific focus is due to the reduction in the number of observable signs and symptoms, ranging from an acute respiratory condition to severe pneumonia, showing an efficient form of attribute engineering. It is important to note that the clinical diagnosis can vary from asymptomatic to extremely harsh conditions. About 80% of patients with Covid-19 may be asymptomatic or have few symptoms. Approximately 20% of the detected cases require hospital care because they have difficulty breathing, of which about 5% may require ventilatory support in the Intensive Care Unit. Also, the present study proposes a hybrid approach model, structured in the composition of Artificial Intelligence techniques, using Machine Learning algorithms, associated with multicriteria methods of decision support based on the Verbal Decision Analysis methodology, aiming at the discovery of knowledge, as well as exploring the predictive power of specific data in this study, to optimise the diagnostic models of Covid-19. Thus, the model will provide greater accuracy to the diagnosis sought through clinical observation.info:eu-repo/semantics/publishedVersio

Logística e análise multicritério: uma forma de avaliar os serviços de outsourcing

O uso de serviços logísticos terceirizados, mediante a contratação de Operadores Logísticos (OL), vem crescendo nas organizações. Isso porque, ao interferir na precificação dos produtos, a terceirização (ou serviços de outsourcing) da logística tem implicado em vantagens competitivas, fazendo-se necessário avaliá-lo. Para tanto, utilizando o método MCDA e da abordagem Macbeth, a pesquisa propõe um modelo multicritério para avaliar os serviços de outsourcing voltados para logística, com vistas à sua otimização

Como um modelo de análise multicritério pode otimizar a lucratividade de um laboratório de análises clínicas

Laboratórios de análises clínicas são negócios complexos e inseridos em um mercado altamente competitivo e inovador. Sendo assim, é crucial que os gestores desse tipo de empresa trabalhem para garantir o aumento de seus lucros sem prejuízo da qualidade dos serviços prestados. Utilizando o método Macbeth de análise multicritério, a pesquisa buscou criar um modelo ordenado de fatores capazes de influenciar significativamente na lucratividade de um laboratório de análises clínicas de pequeno porte