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Aggregate planning and forecasting in make-to-order production systems

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  • Gansterer, Margaretha

Abstract

In hierarchical production planning (HPP) systems, aggregate production planning (APP) is meant to balance capacity requirements and production quantities for medium term planning horizons. Aggregate plans provide the basic input for further planning steps. In recent years researchers came up with comprehensive models and sophisticated solution methods for this kind of high level planning. However, some practitioners claim that the aggregate planning concept is rarely applied in industry.

Suggested Citation

  • Gansterer, Margaretha, 2015. "Aggregate planning and forecasting in make-to-order production systems," International Journal of Production Economics, Elsevier, vol. 170(PB), pages 521-528.
    • Handle: RePEc:eee:proeco:v:170:y:2015:i:pb:p:521-528
    DOI: 10.1016/j.ijpe.2015.06.001
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    References listed on IDEAS

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    2. Yasser A. Davizón & César Martínez-Olvera & Rogelio Soto & Carlos Hinojosa & Piero Espino-Román, 2015. "Optimal Control Approaches to the Aggregate Production Planning Problem," Sustainability, MDPI, vol. 7(12), pages 1-16, December.
    3. Pereira, Daniel Filipe & Oliveira, José Fernando & Carravilla, Maria Antónia, 2020. "Tactical sales and operations planning: A holistic framework and a literature review of decision-making models," International Journal of Production Economics, Elsevier, vol. 228(C).
    4. Ata Allah Taleizadeh, 2017. "Stochastic Multi-Objectives Supply Chain Optimization with Forecasting Partial Backordering Rate: A Novel Hybrid Method of Meta Goal Programming and Evolutionary Algorithms," Asia-Pacific Journal of Operational Research (APJOR), World Scientific Publishing Co. Pte. Ltd., vol. 34(04), pages 1-28, August.
    5. Murray, Paul W. & Agard, Bruno & Barajas, Marco A., 2018. "ASACT - Data preparation for forecasting: A method to substitute transaction data for unavailable product consumption data," International Journal of Production Economics, Elsevier, vol. 203(C), pages 264-275.
    6. Andrea Borenich & Peter Greistorfer & Marc Reimann, 2020. "Model-based production cost estimation to support bid processes: an automotive case study," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 28(3), pages 841-868, September.
    7. Rahmer, Bruno de Jesús & Garzón Saénz, Hernando & Garzón Solana, José Manuel, 2022. "Análisis comparativo de modelos de planificación agregada. El caso de las empresas manufactureras colombianas [Comparative analysis of agreggate planning models. The case of the colombian manufactu," Revista de Métodos Cuantitativos para la Economía y la Empresa = Journal of Quantitative Methods for Economics and Business Administration, Universidad Pablo de Olavide, Department of Quantitative Methods for Economics and Business Administration, vol. 33(1), pages 285-309, June.
    8. Rusindiyanto, 2023. "Production Planning and Control of Flooring Using Aggregate Planning Method," Technium, Technium Science, vol. 16(1), pages 397-404.
    9. Klaus Altendorfer & Thomas Felberbauer & Herbert Jodlbauer, 2018. "Effects of forecast errors on optimal utilisation in aggregate production planning with stochastic customer demand," Papers 1812.00773, arXiv.org.

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