A general resource-constrained scheduling framework for multistage batch facilities with sequence-dependent changeovers

This work introduces a new MILP sequential approach to the short-term scheduling of multistage batch plants that accounts for sequence-dependent changeover times, intermediate due dates and limited availability of renewable resources. It relies on a continuous-time formulation based on the general p...

Descripción completa

Detalles Bibliográficos
Autores: Marchetti, Pablo Andres, Cerda, Jaime
Tipo de recurso: artículo
Estado:Versión publicada
Fecha de publicación:2009
País:Argentina
Institución:Consejo Nacional de Investigaciones Científicas y Técnicas
Repositorio:CONICET Digital (CONICET)
Idioma:inglés
OAI Identifier:oai:ri.conicet.gov.ar:11336/76360
Acceso en línea:http://hdl.handle.net/11336/76360
Access Level:acceso abierto
Palabra clave:Milp Optimization Model
Multiproduct Batch Plant
Resource-Constrained Scheduling
https://purl.org/becyt/ford/2.4
https://purl.org/becyt/ford/2
Descripción
Sumario:This work introduces a new MILP sequential approach to the short-term scheduling of multistage batch plants that accounts for sequence-dependent changeover times, intermediate due dates and limited availability of renewable resources. It relies on a continuous-time formulation based on the general precedence notion that uses different sets of binary variables to handle allocation and sequencing decisions. To avoid resource overloading, additional constraints in terms of sequencing variables and a new set of 0-1 overlapping variables are presented. They allow tracking the set of tasks requiring the same resource and running in parallel at the start of another process operation. In this way, the proposed formulation involves a reasonable number of binary variables and constraints and features a very good computational behavior, even in the presence of hard bottleneck resources. Four illustrative examples, one of them including multiple bottleneck resources shared by several processing stages, have been efficiently solved.