A literature review of existing state-of-the-art approaches for the dynamic scheduling and rescheduling problem

[EN] This paper reviews existing state-of-the-art articles that address the dynamic scheduling (DS) and rescheduling (RS) problem. Unlike traditional static scheduling, which assumes fixed and predictable conditions, DS must continuously adapt to operational disruptions. In actual industrial environ...

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Detalles Bibliográficos
Autores: Fiesco-Muñoz, Juan Pablo|||0009-0008-3369-4607, Esteso, Ana|||0000-0003-0379-8786, Poler, R.|||0000-0003-4475-6371
Tipo de recurso: artículo
Fecha de publicación:2025
País:España
Institución:Universitat Politècnica de València (UPV)
Repositorio:RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia
Idioma:inglés
OAI Identifier:oai:dnet:riunet______::efa2ce88f2fe838db9c3f9500b5c806b
Acceso en línea:https://riunet.upv.es/handle/10251/235270
Access Level:acceso embargado
Palabra clave:Dynamic scheduling
Rescheduling
Smart manufacturing
Sustainability
Descripción
Sumario:[EN] This paper reviews existing state-of-the-art articles that address the dynamic scheduling (DS) and rescheduling (RS) problem. Unlike traditional static scheduling, which assumes fixed and predictable conditions, DS must continuously adapt to operational disruptions. In actual industrial environments and smart manufacturing (SM) factories, real-time adjustments are necessary to optimize production and resource usage. This review analyzes 10 state-of-the-art, selected for their explicit focus on DS/RS, detailed methodology, and relevance to SM and sustainability. The results highlight the existence of different terminologies for the DS problem and the absence of a standardized framework to classify all its characteristics. It was also found that the state of the art does not provide detailed and clear analyses of the integration of SM technologies into real-world manufacturing challenges. The approaches to sustainability aspects in the reviews analyzed focus on different aspects, such as energy efficiency, resource use and alignment with the SDGs, highlighting the need for a more holistic approach. The paper proposes future research directions, including updated reviews that integrate SM technologies, sustainability, and a standardized framework, encompassing real-time data, robust and agile tools, artificial intelligence and internet of things.