An inverse S curve based search mechanism on particle swarm optimization for solving project scheduling problem

The multi-mode resource-constrained project scheduling problem (MRCPSP) has been confirmed to be an NP-hard problem, and has been widely studied. The particle swarm optimization is an effective method and well applied to solve all kind of scheduling problems. MRCPSP is regarded as two sub-problems: the activity mode selection and the activity priority sub-problems. Therefore, discrete version PSO and conventional PSO were used for solving these two sub-problems respectively. In discrete version PSO, the velocity update rule based on constriction PSO is applied. Meanwhile, an inverse S curve based inertia weight adjustment mechanism was proposed to enhance both the global search and local search to improve search efficiency. Moreover, a grouped communication topology was designed to avoid premature convergence and slow convergence problems, i.e., to balance convergence rate. Instances of MRCPSP in PSPLIB were tested to verify the performance of the proposed scheme. The experimental results confirmed that the proposed scheme is effective and efficient for solving MRCPSP type scheduling problems.