Resource-constrained multi-project scheduling based on ant colony optimization algorithm

Firstly, the model of resource-constrained multi-project scheduling is established. Secondly, a new project priority indicator named project risk ratio synthesizing project throughput and lose per unit of constrained resource is presented. Thirdly, the ant colony optimization (ACO) algorithm is introduced to solve the multi-project scheduling model. Furthermore, in order to accelerate the convergence efficiency and quality of ACO, the project priority indicator of project risk ratio is treated as the heuristic function of ACO, while the adaptive decay coefficient is introduced into the pheromone updating strategy. Simulation results show that the presented approach effectively obtain the optimal scheduling solution and is better than the traditional rule-based scheduling approach.