A multi-pass simulation-based, real-time scheduling and shop floor control system
Transactions of the Society for Computer Simulation International - modeling and simulation in manufacturing
Automatic simulation model generation for simulation-based, real-time shop floor control
Computers in Industry
Introduction to Simulation Using SIMAN
Introduction to Simulation Using SIMAN
Real-Time Design Patterns: Robust Scalable Architecture for Real-Time Systems
Real-Time Design Patterns: Robust Scalable Architecture for Real-Time Systems
UML Bible
Simulation-Based Optimization: Parametric Optimization Techniques and Reinforcement Learning
Simulation-Based Optimization: Parametric Optimization Techniques and Reinforcement Learning
Stability-oriented evaluation of rescheduling strategies, by using simulation
Computers in Industry
Professional Multicore Programming: Design and Implementation for C++ Developers
Professional Multicore Programming: Design and Implementation for C++ Developers
A generic framework for real-time discrete event simulation (DES) modelling
Proceedings of the 40th Conference on Winter Simulation
A survey of dynamic scheduling in manufacturing systems
Journal of Scheduling
Process modeling for simulation
Computers in Industry
| Hi-index | 0.00 |
The paper presents an implemented architecture of an intelligent simulation-based real-time control (SRTC) system for industrial applications. The proposed SRTC uses a trajectory tracking strategy inspired from the model-based predictive control approach. Dynamic control law based on the closed-loop feedback correction is embedded. A computer implementation of this control scheme and experiments are conducted for real-time truck dispatching on a surface mine transportation system. Results showed the capability of the SRTC to generate efficient real-time truck dispatching orders at each 120s. Simulation results demonstrate that managing trucks with such dynamic control law improves productivity. This improvement is reached when the transportation system is under steady as well as transient states conditions. The proposed SRTC makes use of the intelligent metaheuristic optimization search even under tight timeliness constraints.