Utilize este identificador para referenciar este registo:
https://hdl.handle.net/1822/75190
Título: | An intelligent decision support system for production planning in garments industry |
Autor(es): | Ribeiro, Rui Pilastri, André Carvalho, Hugo Matta, Arthur Pereira, Pedro José Rocha, Pedro Alves, Marcelo Cortez, Paulo |
Palavras-chave: | Textile production planning AutoML NSGA-II |
Data: | 2021 |
Editora: | Springer, Cham |
Revista: | Lecture Notes in Computer Science |
Citação: | Ribeiro R. et al. (2021) An Intelligent Decision Support System for Production Planning in Garments Industry. In: Yin H. et al. (eds) Intelligent Data Engineering and Automated Learning – IDEAL 2021. IDEAL 2021. Lecture Notes in Computer Science, vol 13113. Springer, Cham. https://doi.org/10.1007/978-3-030-91608-4_37 |
Resumo(s): | In this paper, we propose an Intelligent Decision Support System (IDSS) that combines prediction and optimization for production planning. We worked with a company that provides software for the garments Industry and that had access to real-world data related with a client that works with subcontractors. Using an Automated Machine Learning (AutoML) approach, we firstly target four predictive tasks that are crucial to estimate production planning indicators. Then, we use historical data and one of the predicted indicators to search for the best subcontractor allocation plan, which minimize both the cost and production time via an Evolutionary Multiobjective Optimization (EMO) algorithm (NSGA-II), achieving interesting results. |
Tipo: | Artigo em ata de conferência |
URI: | https://hdl.handle.net/1822/75190 |
ISBN: | 978-3-030-91607-7 |
e-ISBN: | 978-3-030-91608-4 |
DOI: | 10.1007/978-3-030-91608-4_37 |
ISSN: | 0302-9743 |
Versão da editora: | The original publication is available at: https://link.springer.com/chapter/10.1007%2F978-3-030-91608-4_37 |
Arbitragem científica: | yes |
Acesso: | Acesso aberto |
Aparece nas coleções: |
Ficheiros deste registo:
Ficheiro | Descrição | Tamanho | Formato | |
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ideal63.pdf | 327,57 kB | Adobe PDF | Ver/Abrir |
Este trabalho está licenciado sob uma Licença Creative Commons