Models and algorithms for production planning, scheduling and sequencing problems: a holistic framework and a systematic review

Handle

https://riunet.upv.es/handle/10251/201090

Cita bibliográfica

Guzmán-Ortiz, BE.; Andres, B.; Poler, R. (2022). Models and algorithms for production planning, scheduling and sequencing problems: a holistic framework and a systematic review. Journal of Industrial Information Integration. 27:1-17. https://doi.org/10.1016/j.jii.2021.100287

Titulación

Resumen

[EN] Production planning, scheduling and sequencing comprise the core of the manufacturing companies' perfor-mance. The new and changing market demands make manufacturing a challenge because companies must produce by using the minimum possible number of resources to provide high-quality products and to respond quickly to market demands. Thus the need for efficient production planning, scheduling and sequencing has become a very important research area for companies and researchers in recent decades. We evaluated the current state of such research with a holistic framework that comprised the plans aggregation and disaggregation levels, the modelling approaches to represent the different types of plans and their characteristics, the solution approaches with the adopted algorithms, the application areas, the intra-and inter-enterprise levels of inte-gration, the sizes of the datasets used to validate the models and algorithms, the development tools, and the quality of the solutions obtained in relation to the problems' data size. The systematic literature review is ar -ranged within the framework and grouped around different types of plans, including production planning, scheduling and sequencing, and their combinations. Finally, some gaps in the related research are identified and future research opportunities are proposed.

Fuente

Journal of Industrial Information Integration

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