Task scheduling in multiprocessor systems using inertial velocity differential evolution
XiaohongQiu1, YutingHu2, BoLi1
COMPUTER MODELLING & NEW TECHNOLOGIES 2014 18(12B) 343-349
1Software School, Jiangxi University of Science and Technology, Nanchang 330013, China
2School of Information Engineering, Jiangxi University of Science and Technology,Ganzhou 341000, China
Task scheduling in multiprocessor systems is a challenge NP-complete problem. All practical real-time scheduling algorithms in multiprocessor systems present a trade-off between their computational complexity and performance. In this paper, An improved Differential Evolution algorithm combined Particle Swarm Optimization idea is proposed to solve the Task Scheduling Problem (TSP) in multiprocessor system. The proposed algorithm called Inertial Velocity Differential Evolution (IVDE) consists of an additional inertial velocity factor based on adaptive differential evolution algorithm. IVDE optimizes task scheduling to the minimum of the overall schedule length. The simulation results show that IVDE algorithm not only reduces the computational complexity, but also is easy to get the global optimum compared with GA and Ant Colony Optimizer to solve the task scheduling problem in multiprocessor systems.