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Multi-objective evolutionary algorithm-enabled multi-stage collaborative scheduling for automotive production.

, , , , and . Comput. Ind. Eng., (2024)

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Deep Learning Based Modeling for Cutting Energy Consumed in CNC Turning Process., , , , and . SMC, page 1398-1403. IEEE, (2018)Optimization of CNC machine processing parameters for low carbon manufacturing., , , and . CASE, page 498-503. IEEE, (2013)Meta-Reinforcement Learning of Machining Parameters for Energy-Efficient Process Control of Flexible Turning Operations., , , and . IEEE Trans Autom. Sci. Eng., 18 (1): 5-18 (2021)Process Route Optimization for Generalized Energy Efficiency and Production Time in Machining System., , , , and . SOLI, page 110-115. IEEE, (2019)Uncertainty management in remanufacturing: A review., and . CASE, page 52-57. IEEE, (2012)A collaborative resequencing approach enabled by multi-core PREA for a multi-stage automotive flow shop., , , , and . Expert Syst. Appl., 237 (Part C): 121825 (March 2024)A comprehensive approach to parameters optimization of energy-aware CNC milling., , , , and . J. Intell. Manuf., 30 (1): 123-138 (2019)Special Issue on Intelligent Energy Solutions to Sustainable Production and Service Automation., , , and . IEEE Trans Autom. Sci. Eng., 18 (2): 615-617 (2021)Energy Consumption Prediction of a CNC Machining Process With Incomplete Data., , , , and . IEEE CAA J. Autom. Sinica, 8 (5): 987-1000 (2021)Energy-efficient rescheduling for the flexible machining systems with random machine breakdown and urgent job arrival., , , , and . SMC, page 409-414. IEEE, (2019)