Dynamic job shop scheduling under multiple order disturbances using deep reinforcement learning. [PDF]
Sun Z, Han W, Gao L, Zhu C, Lyu Q.
europepmc +1 more source
A numerical model resulting from irreversible thermodynamics for describing transport processes is introduced, focusing on thermodynamic activity gradients as the actual driving force for diffusion. Implemented in CUDA C++ and using CalPhaD methods for determining the necessary activity data, the model accurately simulates interdiffusion in aluminum ...
Ulrich Holländer +3 more
wiley +1 more source
An improved scatter search algorithm for solving job shop scheduling problems with parallel batch processing machine. [PDF]
Wang H, Xiong H, Zuo W, Shi S.
europepmc +1 more source
Order Management and Completion Date Prediction of Manufacturing Job-Shop Based on Deep Learning.
Wang M.
europepmc +1 more source
A hierarchical porous copper current collector is fabricated via three‐dimensional printing combined with pressureless sintering to stabilize lithium metal anodes. The interconnected architecture lowers local current density, guides uniform Li deposition within pores, and suppresses dendrite growth.
Alok Kumar Mishra, Mukul Shukla
wiley +1 more source
Dual-self-learning co-evolutionary algorithm for energy-efficient flexible job shop scheduling problem with processing- transportation composite robots. [PDF]
Zhang M, Zhou M, Zhang L, Zhang Z.
europepmc +1 more source
A DNA algorithm for the job shop scheduling problem based on the Adleman-Lipton model. [PDF]
Tian X, Liu X, Zhang H, Sun M, Zhao Y.
europepmc +1 more source
Setup‐Optimized Sequencing in Job Shops: Modeling Workstation Productivity and Lateness Behavior
Setup‐optimized sequencing in job‐shop production creates a trade‐off between productivity improvement and schedule reliability. A WIP‐explicit modeling framework links sequencing‐induced productivity gains and lateness dispersion through the production operating curve.
Friederike Stefanowski +2 more
wiley +1 more source
Data-driven automated job shop scheduling optimization considering AGV obstacle avoidance. [PDF]
Tang Q, Wang H.
europepmc +1 more source
A combined finite element and phase‐field approach predicts the evolution of microstructure during the directional solidification of Ni‐based superalloys. The model reveals how withdrawal rate, temperature gradient, and wall thickness control the dendrite spacing, highlighting the strong effect of surface regions in thin sections where dendrite growth ...
Sean Böhm +3 more
wiley +1 more source

