Enhancing the General Precedence Approach for Industrial Scheduling Problems with Sequence-Dependent Issues
This paper presents a novel technique that enhances the general precedence, mixed-integer programming approach for the optimal scheduling of process operations. It proves to effectively solve different types of industrial problems dealing with particular sequence-dependent issues, requiring less com...
| Autores: | , , , |
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| Tipo de recurso: | artículo |
| Estado: | Versión publicada |
| Fecha de publicación: | 2014 |
| País: | Argentina |
| Institución: | Consejo Nacional de Investigaciones Científicas y Técnicas |
| Repositorio: | CONICET Digital (CONICET) |
| Idioma: | inglés |
| OAI Identifier: | oai:ri.conicet.gov.ar:11336/22351 |
| Acceso en línea: | http://hdl.handle.net/11336/22351 |
| Access Level: | acceso abierto |
| Palabra clave: | Milp Approach Sequencing General Precedence Enhanced Formulation https://purl.org/becyt/ford/2.4 https://purl.org/becyt/ford/2 |
| Sumario: | This paper presents a novel technique that enhances the general precedence, mixed-integer programming approach for the optimal scheduling of process operations. It proves to effectively solve different types of industrial problems dealing with particular sequence-dependent issues, requiring less computational effort than other optimization models. The new formulation takes advantage of the general precedence modeling efficiency, overcoming one of its major limitations. |
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