The multi-mode resource-constrained project scheduling problem (MRCPSP) is an important issue for industry, and has been confirmed to be an NP-hard problem. The particle swarm optimization meta-heuristic is an effective and promising method and well applied to solve a variety of NP application problems. MRCPSP involves two sub-problems: the activity mode selection and the activity order sub-problems. Therefore, a discrete version PSO and constriction version PSO were applied for solving these two sub-problems respectively. Discrete PSO is utilized for determining the activity operation mode, the constriction PSO is applied for deciding the activity order. To enhance the exploration and exploitation search so as to improve search efficiency, an S decreasing constriction factor adjustment mechanism was proposed. To verify the performance of proposed scheme, instances of MRCPSP in PSPLIB were tested and comparisons with other state-of-art algorithms were also conducted. The experimental results reveal that the proposed S decreasing constriction factor adjustment scheme is efficient for solving MRCPSP type scheduling problems.
['Reuy-Maw Chen', 'Chuin-Mu Wang']
Controlling Search Using an S Decreasing Constriction Factor for Solving Multi-mode Scheduling Problems