Publicação
Multi-project scheduling under uncertainty and resource flexibility: a systematic literature review
| Resumo: | A Systematic Literature Review (SLR) on the Resource-Constrained Multi-Project Scheduling Problem (RCMPSP), Uncertainty, and Resource Flexibility (human resource) is presented in this study. The main purpose is to help scholars with an overview of existing techniques and to identify new research directions. After applying exclusion criteria, 107 papers were analysed (2013-2023). The methodology adopted for this SRL is PRISMA. Based on the results, the approaches proposed to solve the RCMPSP were classified and the main findings were presented. The results show that the main focus of the existing research has been devoted to approximate algorithms. Genetic algorithms (GAs) and priority rules (PRs) are the most representative approximate algorithms, with 39% and 18%, respectively. At the same time, mixed integer programming (MIP) (9%) and branch & bound (B&B) algorithms (4%) are the most used exact algorithms. This analysis provides a vivid roadmap for future research based on the collected papers. |
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| Autores principais: | Aghileh, Marzieh |
| Outros Autores: | Tereso, Anabela Pereira; Alvelos, Filipe Pereira e; Monteiro Lopes, Maria Odete |
| Assunto: | Multi-project scheduling resource-constrained multi-project scheduling problem (RCMPSP) uncertainty resource flexibility systematic literature review (SLR) |
| Ano: | 2024 |
| País: | Portugal |
| Tipo de documento: | artigo |
| Tipo de acesso: | acesso aberto |
| Instituição associada: | Universidade do Minho |
| Idioma: | inglês |
| Origem: | RepositóriUM - Universidade do Minho |
| Resumo: | A Systematic Literature Review (SLR) on the Resource-Constrained Multi-Project Scheduling Problem (RCMPSP), Uncertainty, and Resource Flexibility (human resource) is presented in this study. The main purpose is to help scholars with an overview of existing techniques and to identify new research directions. After applying exclusion criteria, 107 papers were analysed (2013-2023). The methodology adopted for this SRL is PRISMA. Based on the results, the approaches proposed to solve the RCMPSP were classified and the main findings were presented. The results show that the main focus of the existing research has been devoted to approximate algorithms. Genetic algorithms (GAs) and priority rules (PRs) are the most representative approximate algorithms, with 39% and 18%, respectively. At the same time, mixed integer programming (MIP) (9%) and branch & bound (B&B) algorithms (4%) are the most used exact algorithms. This analysis provides a vivid roadmap for future research based on the collected papers. |
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