Research on a resource-constrained project scheduling problem in a hazardous environment and its staffing strategies based on PSO algorithm

We study a resource-constrained project scheduling problem in a hazardous environment considering some different strategies of staffing. An overhaul project of a nuclear power plant is chosen as a typical example. The same as the conventional projects scheduling, the problem is constrained by the availability of resources. However, due to the unique working environment in this project, the availability of resources is constrained by the accumulated amount of harm that the workers could withstand. As this extremely increases the complexity of the problem. In order to address the investigated problem, we propose a novel particle swarm optimization algorithm: probable mechanism-based discrete particle swarm optimization algorithm (PMPSO). The PMPSO algorithm is a discretization form of the traditional particle swarm optimization (PSO) algorithm. We use the PMPSO algorithm to solve the problem thinking of nine combinations of staffing strategies respectively. Comparison experiments of the combination of staffing strategies show that strategy of ‘3’ outperforms the other strategies. Numerical experiments indicate the adaptability of the PMPSO algorithm and the validity of the conclusion