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- A new contribution for solving dynamic scheduling problems using a Tabu searchPublication . Madureira, Ana Maria; Ramos, Carlos; Silva, Sívio do CarmoMany real-world optimisation problems are eventually dynamic. New jobs are to be added to the schedule, the quality of the raw material may be changing, new orders have to be included into the problem etc. In such cases, when the problem changes over the course of the optimisation, the purpose of the optimisation algorithm changes from finding an optimal solution to being able to continuously track the movement of the optimum through time. This paper starts by presenting a new scheduling method based on Tabu Search for the resolution of the dynamic Job-Shop Scheduling Problem, which considers job release times, job due dates and different assembly levels (parallel operations). This framework is based on a decomposition of the Job-Shop Scheduling Problem into a series of deterministic Single Machine Scheduling Problem (SMSP) and on a Tabu Search Algorithm, which solves each SMSP whose solutions are, then, integrated. An inter-machine activity coordination mechanism is described. Finally, the used approach adapts the resolution of the deterministic problem to the non-deterministic one in which changes may occur continually. This takes into account dynamic occurrences in a manufacturing system and adapts the current neighbourhood to a new regenerated neighbourhood.
- A genetic approach to dynamic scheduling for total weighted tardiness problemPublication . Madureira, Ana Maria; Ramos, Carlos; Silva, Sílvio do Carmo; Petley, Gary; Coddington, Alexandra; Aylett, RuthThis paper presents several local search metaheuristics for the problem of scheduling a single machine to minimise total weighted tardiness. A genetic algorithm for the static single machine total weighted tardiness problem is presented, and a multistart version named metaGA is proposed. The obtained computational results permit to conclude about their efficiency and effectiveness. The resolution of the dynamic single machine total weighted tardiness problem using a scheduling system based on Genetic Algorithms (GA) is proposed. This approach extends the resolution of static Single Machine Scheduling Problems (SMSP) to dynamic SMSP in which changes can occur continually. A new population generating mechanism for dynamic environments is proposed. This method takes into account dynamic occurrences in a system, and adapts the current modified population into a new regenerated population.
- A new framework for dynamic deterministic job-shop scheduling problems using genetic algorithmsPublication . Madureira, Ana Maria; Ramos, Carlos; Silva, Sílvio do Carmo; Verdejo, Vicente; Gonzalez, Francisco; Sorlí, M. Pilar; Alarcó, M. Angeles; Alfaro, M. SacramentoThe problem of finding good solutions to scheduling problems is very important to real manufacturing systems, since the production rate and production costs are very dependent on the schedules used for controlling the work in the system. Most research in scheduling focuses on optimisation of static problems, where all problem data are known before scheduling starts. However many real world optimisation problems are dynamic, in which changes may occur continually. This paper presents a scheduling system, based on Genetic Algorithms for the resolution of the deterministic Job-Shop Scheduling Problem (JSSP), which considers the existence of different job release dates and job due dates, and different assembly levels. This approach is based on a decomposition of the Job-Shop Scheduling Problem into a series of deterministic Single Machine Scheduling Problem (SMSP). A Genetic Algorithm (GA) solves each SMSP, and the obtained solutions are integrated at the end. A coordination mechanism is proposed.
- A new contribution for solving dynamic scheduling problems using genetic algorithmsPublication . Madureira, Ana Maria; Ramos, Carlos; Silva, Sílvio do CarmoScheduling is an important element of manufacturing systems because it allows to improve the system performance and serves as an overall plan on which system activities are based. The main purpose of this paper isto explore the use of evolutionary computation techniques for solving real world optimisation problems. These classes of problems have additional difficulties for the traditional optimisation techniques. This paper presents a simple and general framework based on Genetic Algorithms to solve dynamic Job-Shop scheduling problems. A new generation of initial individual and population is proposed. The proposed framework adapts the resolution of the deterministic problem to the non-deterministic one in which changes may occur continually. This takes into account dynamic occurrences in a manufacturing system and adapts the current population.
- Vertical scheduling approach to dynamic scheduling problems using Tabu searchPublication . Madureira, Ana Maria; Ramos, Carlos; Silva, Sílvio C.[Abstract exerpt] In recent years, there have been significant advances in the theory and the application of Meta-Heuristics to solve hard optimization problems. Most of the heuristic or approximation methods proposed for Job- Shop Scheduling problems are tailored techniques, i.e. developed specifically for a problem in consideration. There is a need to develop robust and flexible methods capable of being applicable not only to a specific problem and environment but also to a variety of scheduling problems and environments.
- Using tabu search for dynamic scheduling: the extended job-shop scheduling problemPublication . Madureira, Ana Maria; Ramos, Carlos; Silva, Sílvio do Carmo; Kendall, Graham; Burke, Edmund; Petrovic, SanjaIn most practical environments, scheduling is an ongoing reactive process where the presence of real time information continually forces reconsideration and revision of pre-established schedules. Scheduling algorithms that achieve good or near optimal solutions and can efficiently adapt them to perturbations are, in most cases, preferable to those that achieve optimal ones but that cannot implement such an adaptation. This reality, motivated us to concentrate on tools, which could deal with such dynamic, disturbed scheduling problems, both for single and multi-machine manufacturing settings, even though, due to the complexity of these problems, optimal solutions may not be possible to find. We decided to address the problem drawing upon the potential of Tabu Search to deal with such complex situations.
- A GA based approach for dynamic job-shop scheduling problemsPublication . Madureira, Ana Maria; Ramos, Carlos; Silva, Sílvio Carmo[Abstract excerpt] Most research in Genetic Algorithms (GA) focuses on optimisation of static scheduling problems. Since Davis proposed the first Genetic Algorithm to address scheduling problems in 1985, GA have been widely used in manufacturing scheduling applications. However, most of he works deal with optimisation of the scheduling problem in static environments, whereas many real world problems are dynamic, frequently subject to several sorts of random occurrences and perturbations, such as random job releases, machine breakdowns, jobs cancellation and due date and time processing changes.
- Braço ótico com controle Arduíno para medição do índice de refraçãoPublication . Moreira, Ana Rita; Ramos, Carlos; Oliveira Vilão de Ramos, Gina MariaA automação em contexto laboratorial tem reforçado a precisão e a reprodutibilidade das medições no domínio biomédico. Neste trabalho descreve-se um sistema robótico automatizado para determinar o índice de refração de tecidos biológicos através do ângulo de Brewster, integrando controlo motorizado, aquisição sensorial e análise computacional. O protótipo, composto por motores de passo controlados por Arduino e por um fotodetetor com processamento em tempo real numa interface Python, realiza varrimentos angulares sincronizados e identifica autonomamente o ponto mínimo de refletância, completando todo o ciclo de medição. Em material de referência obteve-se um ângulo de Brewster de 56,2° e um índice de 1,495 com erro inferior a 0,5%, enquanto nos ensaios com tecido muscular os valores variaram entre 1,375 e 1,393, refletindo a influência da orientação das fibras. Os resultados confirmam a precisão e a repetibilidade do sistema, demonstrando o seu potencial como solução acessível para caracterização ótica de tecidos biológicos.
- NutriScan: Nutrition analysis systemPublication . Ribeiro, Hugo; Soares, Filipe; Mendes, Gonçalo; Serra, João; Neves, Mariana; Gonçalves, TiagoGrowing public awareness of the connection between diet and health has increased the need for accessible and comprehensible nutritional information. To address this, we developed NutriScan, a web-based expert system designed to provide real-time nutritional analysis of food products. The system integrates barcode recognition with a knowledge base powered by Drools and Prolog inference engines, enabling intelligent reasoning over nutritional data. NutriScan offers detailed product evaluations and scoring. Through personalized user profiles, it identifies potential allergens, generates tailored alerts, and suggests healthier alternatives. The architecture combines both Java (Drools) and Prolog inference back-end components to explore the impact of two different technologies over AI techniques. The system demonstrates the integration of symbolic AI through Prolog-based logical inference and a structured knowledge database, showcasing how expert systems can deliver transparent, rule-driven nutritional analysis and decision support. While both Drools and Prolog can be applied to rule-based reasoning, their underlying mechanisms differ substantially: Prolog employs backward chaining for logic-based inference, facilitating complex reasoning and knowledge representation, whereas Drools applies forward chaining to enable efficient, scalable rule evaluation with greater implementation clarity. Overall, NutriScan leverages expert system principles and AI reasoning to support informed and health-conscious consumer decisions. The successful development and validation of NutriScan highlight the effectiveness of combining distinct inference paradigms to create intelligent, user-oriented decision-support tools.
- Simulação de eletrocardiograma com o modelo de McSharryPublication . Hayashida, Camila; Almeida, Lícia; Nogueira, Sofia; Ramos, Carlos; Oliveira Vilão de Ramos, Gina MariaO presente estudo teve como objetivo desenvolver um sistema de simulação de sinais ECG baseados no modelo matemático de McSharry, recorrendo a dois métodos numérico distintos: Euler Maruyama, na sua formulação estocástica, e Runge Kutta, enquanto referência determinística. O estudo focou-se em avaliar a capacidade destes métodos para gerar sinais ECG realistas e fisiologicamente plausíveis, tanto em condições normais como em cenários patológicos, nomeadamente taquicardia, através da modulação apropriada dos parâmetros intrínsecos do modelo. Para analisar a comparações entre os métodos foram implementadas métricas abrangentes no domínio temporal e espectral, incluindo erro quadrático médio, erro absoluto médio, coeficientes de correlação, análise de intervalos RR, amplitudes dos picos R. Os resultados demonstraram que ambos os métodos produzem sinais com morfologia consistente com registos reais, evidenciando uma reprodução fidedigna das ondas P, QRS e T. O método Runge Kutta forneceu uma trajetória determinística suave e estável, enquanto o método Euler Maruyama introduziu variabilidade ciclo a ciclo semelhante à observada em sinais biológicos, reforçando a relevância da modelação estocástica para simulação de fenómenos cardíacos. A análise evidenciou, no entanto, que alguns coeficientes de amplitude associados ao modelo necessitam de refinamento para assegurar plena coerência fisiológica ao nível das ondas PQRST. Apesar destas limitações, concluiu-se que a modelação matemática constitui uma abordagem promissora para a simulação de sinais ECG, com potencial para aplicações futuras em diagnóstico e monitorização cardíaca, apesar das limitações associadas aos métodos numéricos e ao próprio modelo.