Título: | A HEURISTIC METHOD FOR MULTIOBJECTIVE SCHEDULING PROBLEM IN VARIOUS MACHINE ENVIRONMENTS | |||||||
Autor: |
MIGUEL ANGEL FERNANDEZ PEREZ |
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Colaborador(es): |
FERNANDA MARIA PEREIRA RAUPP - Orientador |
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Catalogação: | 04/JUN/2012 | Língua(s): | PORTUGUESE - BRAZIL |
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Tipo: | TEXT | Subtipo: | THESIS | |||||
Notas: |
[pt] Todos os dados constantes dos documentos são de inteira responsabilidade de seus autores. Os dados utilizados nas descrições dos documentos estão em conformidade com os sistemas da administração da PUC-Rio. [en] All data contained in the documents are the sole responsibility of the authors. The data used in the descriptions of the documents are in conformity with the systems of the administration of PUC-Rio. |
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Referência(s): |
[pt] https://www.maxwell.vrac.puc-rio.br/projetosEspeciais/ETDs/consultas/conteudo.php?strSecao=resultado&nrSeq=19601&idi=1 [en] https://www.maxwell.vrac.puc-rio.br/projetosEspeciais/ETDs/consultas/conteudo.php?strSecao=resultado&nrSeq=19601&idi=2 |
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DOI: | https://doi.org/10.17771/PUCRio.acad.19601 | |||||||
Resumo: | ||||||||
The production scheduling problem aims to determine a feasible sequence
operation processes and resources over a period of time to optimize one or more
measures of performance, usually associated with the time factor or balancing the
use of resources. In this problem, precedence constraints between operations and
availability of resources per operation may exist. Such operations are part of the
tasks or customer orders for products or services. Scheduling problems can be
difficult, particularly because time is a limiting factor to get the best sequence
among possible feasible sequences. However, finding good solutions for complex
optimization problems in an acceptable amount time is crucial in competitive
production systems, where the scheduling problems are usually found. The
dissertation is focused on the development of a new computational method for
solving scheduling problems in the operations environments: flow shop, flexible
job shop, integrated resource selection and operation sequences and advanced
planning and scheduling. Inspired by Newton s method for continuous
multiobjective optimization problems of Fliege et al. (2008), the proposed method
is adapted to each operating environment. Examples and numerical experiments
with the proposed method are presented for each operating environment, showing
some comparisons with existing algorithms, as well.
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