Particle swarm optimization for preemptive project scheduling with resource constraints

This paper studies preemptive project scheduling with resource constraints. We developed a particle swarm optimization (PSO) method based on two different particle representations to solve the problem which permits each activity to preempt at most once. Computational experiments are provided to investigate the performance of PSO-based approaches and to compare two representations. The result shows that preemption helps to reduce project duration and the PSO method we developed can handle preemptive project scheduling efficiently.