A GENETIC ALGORITHM FOR THE ONE-DIMENSIONAL CUTTING STOCK PROBLEM WITH SETUPS
This paper investigates the one-dimensional cutting stock problem considering two conflicting objective functions: minimization of both the number of objects and the number of different cutting patterns used. A new heuristic method based on the concepts of genetic algorithms is proposed to solve the...
| Autores: | , , |
|---|---|
| Tipo de recurso: | artículo |
| Estado: | Versión publicada |
| Fecha de publicación: | 2014 |
| País: | Brasil |
| Institución: | Universidade Federal de São Paulo (UNIFESP) |
| Repositorio: | Repositório Institucional da UNIFESP |
| Idioma: | inglés |
| OAI Identifier: | oai:repositorio.unifesp.br:11600/8367 |
| Acceso en línea: | http://dx.doi.org/10.1590/0101-7438.2014.034.02.0165 http://repositorio.unifesp.br/handle/11600/8367 |
| Access Level: | acceso abierto |
| Palabra clave: | integer optimization cutting stock problem with setups genetic algorithm |
| Sumario: | This paper investigates the one-dimensional cutting stock problem considering two conflicting objective functions: minimization of both the number of objects and the number of different cutting patterns used. A new heuristic method based on the concepts of genetic algorithms is proposed to solve the problem. This heuristic is empirically analyzed by solving randomly generated instances and also practical instances from a chemical-fiber company. The computational results show that the method is efficient and obtains positive results when compared to other methods from the literature. |
|---|