Considering the multi-restraints among sub-tasks in parallel and distributed systems, a coevolutionary genetic algorithm (CGA) for tasks matching and scheduling is proposed based on computational model of cooperative coevolution. Simulation results show that the CGA is more effective than the conventional single population-based genetic algorithm (SGA) for multi-tasks matching and scheduling, and the algorithm is of practical use in engineering.