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IIE Transactions Volume 38, 2006 - Issue 9
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ORIGINAL ARTICLES

An efficient priority rule for scheduling job shops to minimize mean tardiness

M. X. Weng Department of Industrial and Management Systems Engineering, University of South Florida, Tampa, FL, 33620, USA
&
Haiying Ren Department of Industrial and Management Systems Engineering, University of South Florida, Tampa, FL, 33620, USA
Pages 789-795 | Received 01 Jun 1999, Accepted 01 Oct 2005, Published online: 23 Feb 2007

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Jianghua Zhang, Son Duy Dao, Wei Zhang, Mark Goh, Guodong Yu, Yan Jin & Weibo Liu. (2023) A new job priority rule for the NEH-based heuristic to minimize makespan in permutation flowshops. Engineering Optimization 55:8, pages 1296-1315.
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Yanmei Cui, Xupeng Zhang & Jing Luo. (2022) Filling Process Optimization through Modifications in Machine Settings. Processes 10:11, pages 2273.
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Taehoon Kim, Yong-Woo Kim, Dongmin Lee & Minju Kim. (2022) Reinforcement learning approach to scheduling of precast concrete production. Journal of Cleaner Production 336, pages 130419.
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Branislav Micieta, Jolanta Staszewska, Matej Kovalsky, Martin Krajcovic, Vladimira Binasova, Ladislav Papanek & Ivan Antoniuk. (2021) Innovative System for Scheduling Production Using a Combination of Parametric Simulation Models. Sustainability 13:17, pages 9518.
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Quang-Vinh Dang, Thijs van Diessen, Tugce Martagan & Ivo Adan. (2021) A matheuristic for parallel machine scheduling with tool replacements. European Journal of Operational Research 291:2, pages 640-660.
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Taehoon Kim, Yong-Woo Kim & Hunhee Cho. (2021) A simulation-based dynamic scheduling model for curtain wall production considering construction planning reliability. Journal of Cleaner Production 286, pages 124922.
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Jiri Stastny, Vladislav Skorpil, Zoltan Balogh & Richard Klein. (2021) Job Shop Scheduling Problem Optimization by Means of Graph-Based Algorithm. Applied Sciences 11:4, pages 1921.
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Taehoon Kim, Yong-woo Kim & Hunhee Cho. (2020) Dynamic production scheduling model under due date uncertainty in precast concrete construction. Journal of Cleaner Production 257, pages 120527.
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Zhaoxia GuoZhaoxia Guo. 2016. Intelligent Decision-making Models for Production and Retail Operations. Intelligent Decision-making Models for Production and Retail Operations 233 260 .
Zhaoxia GuoZhaoxia Guo. 2016. Intelligent Decision-making Models for Production and Retail Operations. Intelligent Decision-making Models for Production and Retail Operations 115 145 .
Zhaoxia GuoZhaoxia Guo. 2016. Intelligent Decision-making Models for Production and Retail Operations. Intelligent Decision-making Models for Production and Retail Operations 1 18 .
R.L. Burdett & E. Kozan. (2015) Techniques to effectively buffer schedules in the face of uncertainties. Computers & Industrial Engineering 87, pages 16-29.
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Z.X. Guo, E.W.T. Ngai, Can Yang & Xuedong Liang. (2015) An RFID-based intelligent decision support system architecture for production monitoring and scheduling in a distributed manufacturing environment. International Journal of Production Economics 159, pages 16-28.
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W.K. Wong, Z.X. Guo & S.Y.S Leung. (2014) Intelligent multi-objective decision-making model with RFID technology for production planning. International Journal of Production Economics 147, pages 647-658.
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Hongwei Ge & Guozhen Tan. 2012. Computational Intelligence Systems in Industrial Engineering. Computational Intelligence Systems in Industrial Engineering 363 383 .
V. Vinod & R. Sridharan. (2011) Simulation modeling and analysis of due-date assignment methods and scheduling decision rules in a dynamic job shop production system. International Journal of Production Economics 129:1, pages 127-146.
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Adeline T.H. Ang, Appa Iyer Sivakumar & Chao Qi. (2009) Criteria selection and analysis for single machine dynamic on-line scheduling with multiple objectives and sequence-dependent setups. Computers & Industrial Engineering 56:4, pages 1223-1231.
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Adeline T. H. Ang & Appa Iyer Sivakumar. (2007) Online multiobjective single machine dynamic scheduling with sequence-dependent setups using simulation-based genetic algorithm with desirability function. Online multiobjective single machine dynamic scheduling with sequence-dependent setups using simulation-based genetic algorithm with desirability function.

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