Detalhes bibliográficos
| Ano de defesa: |
2011 |
| Autor(a) principal: |
Silva, Marilda Fatima de Souza da
 |
| Orientador(a): |
Pereira, Fabio Henrique
|
| Banca de defesa: |
Sassi, Renato José
,
Nabeta, Silvio Ikuyo
|
| Tipo de documento: |
Dissertação
|
| Tipo de acesso: |
Acesso aberto |
| Idioma: |
por |
| Instituição de defesa: |
Universidade Nove de Julho
|
| Programa de Pós-Graduação: |
Programa de Pós-Graduação de Mestrado e Doutorado em Engenharia de Produção
|
| Departamento: |
Engenharia
|
| País: |
BR
|
| Palavras-chave em Português: |
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| Palavras-chave em Inglês: |
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| Área do conhecimento CNPq: |
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| Link de acesso: |
http://bibliotecatede.uninove.br/tede/handle/tede/162
|
Resumo: |
Since the arising of the Toyota Production System (TPS), known as lean production, and more recently the consumer market demands, manufacturing companies have worked to improve their production processes in order to reduce inventory levels, to eliminate waste and to maintain quality, competitiveness and profit. In this context, the sequencing of production orders is one of the most complex problems facing businesses and it is object of several studies. Thus, this paper presents an alternative approach in resolving this problem, i.e.: to use a simulation model as the objective function in genetic algorithm instead analytical mathematical equation. So, for each situation, will not need to change the equation, but adjust the model and to make a new simulation. Heuristics sequencing rules in job shop environments were considered, with routes, due dates and times of operation generated randomly, in order to determine the best programming technique for performance in relation to the total time of crossing, the total tardiness and the number of tardy jobs. Results corroborate the method adopted. Multi-objective optimization approach is based on the coupling of Genetic Algorithm with an Arena simulation model through the Visual Basic for Application language and the ActiveX Automation controller. |
