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Articles

A critical chain project scheduling method based on a differential evolution algorithm

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Pages 3940-3949 | Received 10 Apr 2013, Accepted 30 Oct 2013, Published online: 06 Dec 2013

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Claudio Szwarcfiter, Yale T. Herer & Avraham Shtub. (2023) Shortening the project schedule: solving multimode chance-constrained critical chain buffer management using reinforcement learning. Annals of Operations Research.
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Bingling She, Bo Chen & Nicholas G. Hall. (2021) Buffer sizing in critical chain project management by network decomposition. Omega 102, pages 102382.
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Wuliang Peng, Jianhui Mu, Liangwei Chen & Jiali Lin. (2021) A novel non-dominated sorting genetic algorithm for solving the triple objective project scheduling problem. Memetic Computing 13:2, pages 271-284.
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S. Aramesh, S.M. Mousavi, V. Mohagheghi, E.K. Zavadskas & J. Antucheviciene. (2021) A soft computing approach based on critical chain for project planning and control in real-world applications with interval data. Applied Soft Computing 98, pages 106915.
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Hiroyuki Goto & Alan T. Murray. (2020) Exact and flexible solution approach to a critical chain project management problem. Constraints 25:3-4, pages 280-297.
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Öncü Hazır & Gündüz Ulusoy. (2020) A classification and review of approaches and methods for modeling uncertainty in projects. International Journal of Production Economics 223, pages 107522.
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Xuejun Hu, Jianjiang Wang & Kaijun Leng. (2019) The Interaction Between Critical Chain Sequencing, Buffer Sizing, and Reactive Actions in a CC/BM Framework. Asia-Pacific Journal of Operational Research 36:03, pages 1950010.
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Joaquín Fuentes, Juan Pedro Ruiz, Nelia Valverde & Elena Navarro. (2019) Estudio del efecto de la estimación del tiempo y el tamaño del búfer de proyecto en el Método de la Cadena Crítica = Study of the effect of tasks duration and project buffer size estimation in the Critical Chain Method. Anales de Edificación 5:1, pages 1.
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Nikolaos E. Karkalos, Angelos P. Markopoulos & J. Paulo DavimNikolaos E. Karkalos, Angelos P. Markopoulos & J. Paulo Davim. 2019. Computational Methods for Application in Industry 4.0. Computational Methods for Application in Industry 4.0 11 31 .
Mohammadreza Ghazvini, Vahidreza Ghezavati, Sadigh Raissi & Ahmad Makui. (2017) An Integrated Efficiency–Risk Approach in Sustainable Project Control. Sustainability 9:9, pages 1575.
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Angela Hsiang-Ling Chen, Yun-Chia Liang & Jose David Padilla. (2017) Using discrete Differential Evolution and entropy to solve the MRCPSP. Using discrete Differential Evolution and entropy to solve the MRCPSP.
Xuejun Hu, Erik Demeulemeester, Nanfang Cui, Jianjiang Wang & Wendi Tian. (2016) Improved critical chain buffer management framework considering resource costs and schedule stability. Flexible Services and Manufacturing Journal 29:2, pages 159-183.
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Xuejun Hu, Nanfang Cui, Erik Demeulemeester & Li Bie. (2016) Incorporation of activity sensitivity measures into buffer management to manage project schedule risk. European Journal of Operational Research 249:2, pages 717-727.
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Junguang Zhang, Xiwei Song & Estrella Díaz. (2016) Project buffer sizing of a critical chain based on comprehensive resource tightness. European Journal of Operational Research 248:1, pages 174-182.
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Junguang Zhang, Saike Jia & Estrella Diaz. (2014) A new buffer sizing approach based on the uncertainty of project activities. Concurrent Engineering 23:1, pages 3-12.
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Zheng Zheng, Ze Guo, Yueni Zhu & Xiaoyi Zhang. (2014) A critical chains based distributed multi-project scheduling approach. Neurocomputing 143, pages 282-293.
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