Mathematical programming modelling of the response time variability problem

The Response Time Variability Problem (RTVP) is a scheduling problem that has recently been defined in the literature. The RTVP has a broad range of real-life applications. For example, in the automobile industry it an be used to sequence the models to be produced on a mixed-model assembly line. A p...

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Detalles Bibliográficos
Autores: Corominas Subias, Albert|||0000-0002-4795-7761, Pastor Moreno, Rafael|||0000-0002-6188-4458, Kubiak, Wieslaw
Tipo de recurso: informe técnico
Fecha de publicación:2006
País:España
Institución:Universitat Politècnica de Catalunya (UPC)
Repositorio:UPCommons. Portal del coneixement obert de la UPC
Idioma:inglés
OAI Identifier:oai:upcommons.upc.edu:2117/408
Acceso en línea:https://hdl.handle.net/2117/408
Access Level:acceso abierto
Palabra clave:Time study
Response time variability
Fair sequences
Optimisation
Scheduling
Optimización
Optimització
Seqüenciació
Secuenciación
RTVP
MILP
Heurística -- Informes tècnics
Estudi de temps -- Informes tècnics
Treball -- Organització -- Informes tècnics
Optimització matemàtica -- Informes tècnics
Àrees temàtiques de la UPC::Economia i organització d'empreses::Direcció d’operacions::Control estadístic de processos
Descripción
Sumario:The Response Time Variability Problem (RTVP) is a scheduling problem that has recently been defined in the literature. The RTVP has a broad range of real-life applications. For example, in the automobile industry it an be used to sequence the models to be produced on a mixed-model assembly line. A previous study developed a position exchange heuristic to apply to certain greedy initial sequences for the RTVP. Some mathematical programming models (MILPs) have also been tested to solve it to optimality, but the practical limit to obtaining optimal solutions is 25 units to be scheduled. This paper aims to improve the best mathematical programming model developed thus far in order to solve larger instances up to 40 units to optimality. The contribution of this paper is threefold: i) larger instances can be solved to optimality; ii) the new optimal solution of the RTVP can be used to compare the results of heuristics procedures; and iii) the importance of modelling is demonstrated, as well as the huge impact that reformulation, redundant constraints and the elimination of symmetries have on efficiency of MILPs.