Hybrid particle swarm optimization for preemptive resource-constrained project scheduling
We propose a PSO procedure to solve the preemptive project scheduling problem. Four particle representations are designed for the PSO procedure. Two schedule generation schemes are adopted to decode the representations. The peak crossover operator from genetic algorithms is adopted to update particles. To our knowledge, this is the first extensive experiment on all PSPLIB sets.
particle swarm optimization project scheduling peak crossover preemption