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Estimation of processing time using machine learning and real factory data for optimization of parallel machine scheduling problem

Yamashiro, Hirochika; Nonaka, Hirofumi - In: Operations research perspectives 8 (2021), pp. 1-9

Traditionally, mathematical optimization methods have been applied in manufacturing industries where production scheduling is one of the most important problems and is being actively researched. Extant studies assume that processing times are known or follow a simple distribution. However, the...

Persistent link: https://www.econbiz.de/10012596666

A predictive and prescriptive analytical framework for scheduling language medical interpreters

Ahmed, Abdulaziz; Frohn, Elizabeth - In: Health care management science : a new journal serving … 24 (2021) 3, pp. 531-550

Persistent link: https://www.econbiz.de/10012616313

Parametric forecasting and stochastic programming models for call-center workforce scheduling

Gans, Noah; Shen, Haipeng; Zhou, Yong-Pin; Korolev, Nikolay - In: Manufacturing & service operations management : M & SOM 17 (2015) 4, pp. 571-588

Persistent link: https://www.econbiz.de/10011388043

Spatio-temporal hydro forecasting of multireservoir inflows for hydro-thermal scheduling

Lohmann, Timo; Hering, Amanda S.; Rebennack, Steffen - In: European journal of operational research : EJOR 255 (2016) 1, pp. 243-258

Persistent link: https://www.econbiz.de/10011530864

A survey on AI-based scheduling models, optimization and prediction for hydropower generation : variants, challenges, and future directions

Villeneuve, Yoan; Séguin, Sara; Chehri, Abdellah - 2022

Persistent link: https://www.econbiz.de/10013502350

Introduction: 2022 Daniel H. Wagner prize for excellence in the practice of advanced analytics and operations research

Bjarnadóttir, Margrét Vilborg; Stone, Lawrence D. - In: INFORMS journal on applied analytics 53 (2023) 5, pp. 333-335

Persistent link: https://www.econbiz.de/10014383146

Stochastic optimization with decision-dependent distributions

Drusvyatskiy, Dmitriy; Xiao, Lin - In: Mathematics of operations research 48 (2023) 2, pp. 954-998

Persistent link: https://www.econbiz.de/10014314968

Combining machine learning and optimization for the operational patient-bed assignment problem

Schäfer, Fabian; Walther, Manuel; Grimm, Dominik; … - In: Health care management science : a new journal serving … 26 (2023) 4, pp. 785-806

Persistent link: https://www.econbiz.de/10015079830

Predicting the solution time of branch-and-bound algorithms for mixed-integer programs

Özaltın, Osman Y.; Hunsaker, Brady; Schaefer, Andrew J. - In: INFORMS journal on computing : JOC 23 (2011) 3, pp. 392-403

Persistent link: https://www.econbiz.de/10009296301

Process parameter prediction via Markov models of sub-activities

Marujo, Lino G.; Qassim, Raad Y. - In: RAIRO / Operations research 48 (2014) 3, pp. 303-324

Persistent link: https://www.econbiz.de/10010530199