ISEP – DEI – Comunicações em eventos científicos
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Percorrer ISEP – DEI – Comunicações em eventos científicos por autor "Madureira, Ana Maria"
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- Abordagens ao Problema de Escalonamento em Ambientes Reais de ProduçãoPublication . Madureira, Ana Maria; Almeida, Ana[Resumo] Num sistema de fabrico do tipo Job-Shop podem ser identificados alguns factores que contribuem para a dificuldade do processo de escalonamento, nomeadamente, a complexidade, as restrições e a incerteza. Os ambientes industriais reais são sujeitos a várias fontes de mudança, as quais são tratadas como ocorrências aleatórias, tais como, lançamento de novas ordens de fabrico, avarias, alterações de prioridades, atrasos nas operações, etc. Por escalonamento dinâmico consideramos a situação na qual um plano flexível é executado, isto é, o plano inicial é dinamicamente ajustado (re-escalonado) sempre que eventos inesperados ocorrem no sistema. Esta comunicação tem por objectivo principal efectuar uma sistematização de conceitos e classificações de problemas e tipos de escalonamento, bem como das abordagens usadas na sua resolução. Inicialmente, é apresentado o problema de escalonamento, através da caracterização dos seus elementos e da referência a algumas definições encontradas na literatura, A seguir descrevem-se algumas classificações para os problemas de escalonamento e os tipos de abordagens de resolução a adoptar. Finalmente, são propostas duas arquitecturas para a resolução do problema de escalonamento em ambientes reais de produção caracterizados por um elevado grau de dinamismo. À primeira baseada em Sistemas de Apoio à Decisão e a segunda em Algoritmos Genéticos.
- 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.
- A Genetic Algorithm for the Dynamic Single Machine Scheduling ProblemPublication . Silva, Sílvio do Carmo; Madureira, Ana Maria; Ramos, Carlos; Camarinha-Matos, Luís; Afsarmanesh, Hamideh; Erbe, Heinz-H.This paper starts by studying the performance of two interrelated genetic algorithms (GA) for the static Single Machine Scheduling Problem (SMSP). One is a single start GA, the other, called MetaGA, is a multi-start version GA. The performance is evaluated for total weighted tardiness, on the basis of the quality of scheduling solutions obtained for a limit on computation time. Then, a scheduling system, based on Genetic Algorithms is proposed, for the resolution of the dynamic version of the same problem. The approach used adapts the resolution of the static problem to the dynamic one in which changes may occur continually. This takes into account dynamic occurrences in a system and adapts the current population to a new regenerated population
- A genetic approach for dynamic job-shop scheduling problemsPublication . Madureira, Ana Maria; Ramos, Carlos; Silva, Sílvio do Carmo[Introduction] Since Davis [4] proposed the first Genetic Algorithm(GA) to address scheduling problems in 1985, GAs have been widely used in manufacturing scheduling applications. However, most of the 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. Due to their dynamic nature, real scheduling problems have an additional complexity in relation to static ones. In many situations these problems, even for apparently simple situations, are hard to solve, i.e. the time required to compute an optimal solution increases exponentially with the size of the problem [1]. GAs have been extensively used in the context of Job-Shop Scheduling Problems (JSSP). If all jobs are known before processing starts the JSSP is called static, while if job release times are not fixed at a single point in time, ie. jobs arrive to the system at different times, the problem is called dynamic. Scheduling problems can also be classified as deterministic, when processing times and all other parameters are known and fixed, and stochastic, when some or all parameters are uncertain [7]. The proposed approach deals with these two cases of dynamic scheduling: deterministic and stochastic. For such class of problems, the goal is no longer to find a single optimum, but rather to continuously adapt the solution to the changing environment. The purpose of this paper is to describe an approach based on GA for solving dynamic scheduling problems, where the products (jobs) to be processed have due dates. This paper starts by presenting a scheduling system, based on Genetic Algorithms for the resolution of the dynamic version of Single Machine Scheduling Problem (SMSP). The approach used adapts the resolution of the static problem to the dynamic one in which changes may occur continually. This takes into account dynamic occurrences in a system and adapts the current population to a new regenerated population. Then, it is proposed an approach for the resolution of the Job-Shop Scheduling Problem (JSSP) in dynamic environments. The paper is structured as follows: section 2 provides a description of the considered scheduling problem. Section 3 summarises an approach for the resolution of the Dynamic Single Machine Scheduling Problem. The proposed approach for dynamic scheduling is presented in section 4. Finally, the paper concludes with a summary and some ideas for future work.
- Meta-heuristics for the single-machine scheduling total weighted tardiness problemPublication . Madureira, Ana MariaSome general features of single-machine scheduling problems are described, and some of their structural properties are used to design local search procedures based on alternative definitions of neighbourhoods. In particular, the traditional idea of "exchanging the position of two jobs" is replaced by the idea of "exchanging jobs not apart more than a given number of positions (considered as a parameter of the algorithm)". For generating initial solutions, some traditional priority rules were tested with some degree of randomisation, introducing in general, a positive effect in the performance of the algorithms. Through a set of computational tests, the importance of the different parameters was evaluated, and their values for different meta-heuristic procedures (tabu search, and randomised local search) were tuned. Though these tests have been exhaustive only for a given problem (weighted tardiness), the results already available show these approaches are robust and flexible, and that, in general, satisfactory solutions can be obtained in an efficient way.
- 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.
- 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.