In this paper, a virus coevolution genetic algorithm (multi-mode project scheduling-virus co-evolution genetic algorithm, MPS-VEGA) for the precedence and resource constrained multi-mode project scheduling problem is presented, and the encoding of the solution and the operators such as selection, crossover, mutation and virus_infection are given. MPS-VEGA is used to obtain the optimal scheduling sequences and resource modes for the activities of the project so that the project cost is minimized, which can transmit evolutionary genes not only between parent and child generations vertically by the genetic operators but also in the same generation horizontally by the virus_infection operator so as to perform a global search and a local search, respectively. The schema theorem is adopted to analyze the performance of MPS-VEGA. The theoretical analysis and experimental results show that the MPS-VEGA outperforms the GA. For the multi-mode project scheduling problem with different optimization objectives, MPS-VEGA can simutaneously give standard the optimal scheduling sequences subject to the precedence constraints and the optimal resource modes for the activities of the project.