Embedded PSO for Solving FJSP on Embedded Environment (Industry 4.0 Era)

Since of the advent Industry 4.0, embedded systems have become an indispensable component our life. However, one most significant disadvantages these gadgets is their high power consumption. It was demonstrated that making efficient use device’s central processing unit (CPU) enhances its energy efficiency. The particle swarm optimization (PSO) over environment achieves many resource problems. Difficulties online implementation arise primarily from unavoidable lengthy simulation time to evaluate a candidate solution. In this paper, two-level PSO (E2L-PSO) for intelligent real-time introduced. This algorithm proposed be executed and adapted applications. An automatic adaptation asynchronous CPU completed. Flexible Job Shop Scheduling Problem (FJSP) selected solve, due importance in 4.0 era. analysis run-time performance on handling E2L-PSO STM32F407VG-Discovery card Raspberry Pi B+ conducted. By experimental study, such decreases consumption by 10% 70%, according reduction needed (soft, medium, or hard reduction).