Abstract: Based on the background of Multi-mode Resource Constrained Project Scheduling Problem (MRCPSP), an adaptive hybrid ant colony algorithm is proposed to solve the balance problem between the convergence speed of ant colony algorithm and restraining the possibility of falling into the local optimum. The range of parameters can be adaptively adjusted synchronously with the operation of the algorithm and ants can obtain random parameter values in the parameter value range, forming a hybrid ant colony. The algorithm introduces the pioneer scout ant, reward mechanism of elite ant colony with ranking factor and upper and lower pheromone limits to optimize the pheromone update strategy. At the same time, the time uncertainty problem in MRCPSP can be solved by using this algorithm based on fuzzy theory. Finally, the simulation results show that, compared with other heuristic project scheduling optimization algorithms, this algorithm can improve the global search ability and the quality of solution, and better solve the MRCPSP problem, so it has higher practical application value.

Key words: adaptive parameter, hybrid ant colony, ranking factor, fuzzy theory