Particle Swarm Optimization based Multi-criteria Scheduling for Multi-Core Systems

Multi-criteria scheduling (MCS) is one of the prime concerns for the researchers. The MCS for Multi-Core Systems (McSs) is nondeterministic polynomial (NP)-complete in nature. A nature-inspired intelligent technique, Particle Swarm Optimization (PSO) is used to address the problem. The proposed PSO based multi-criteria scheduling (PSOMCS) algorithm simultaneously considers multiple parameters during the evaluation of fitness function. Particle representation is done in the manner where each particle always produces a complete schedule. The validity of the particle is ensured even after updating of velocity and position. Two different standard benchmark data sets are considered to validate the PSOMCS. The results show that the PSOMCS performs better than several heuristic as well as meta-heuristic algorithms.