Multi-objective Optimization of Multi-Mode Repetitive Project Scheduling

Multi-objective optimization of repetitive project scheduling problem with resource effectiveness is addressed. This problem considers the influence of the duration under work continuity and non-continuity, in order to comply with the relationship of project cost, project makespan and resource effectiveness. To solve the problem, multi-objective repetitive project scheduling model is proposed, and an cloud genetic algorithm is designed, which uses randomness and stability of Normal Cloud Model to generate priority of repetitive project scheduling activities and obtain repetitive project scheduling plan. The results showed that, in repetitive projects under work continuity and non-continuity, the performance comparison shows that the cloud genetic algorithm significantly outperforms the previous multi-objective algorithm.