The reasonable matching of the combat tasks with the platform resources is an important condition for maximizing the operational effectiveness of the combat systems. Considering the difference of cooperation ability between the platforms, the operational effectiveness can be improved greatly if the platforms with high cooperation ability are put together to execute a task. Firstly, the models of cooperation degree between tasks and cooperation ability between platforms are established. Then a task-allocation model is established taking the minimal task completion time, maximal self-cooperation degree within a task and maximal mutual-cooperation degree between the tasks as the objective functions. A hybrid approach is proposed based on Dynamic List Scheduling (DLS) and Chaos Discrete Particle Swarm Optimization (CDPSO) to solve the model, for which DLS is used to select the task needs to be disposed, then CDPSO is used to select the optimal platforms for the selected task. Finally, a simulation is provided to demonstrate the feasibility and validity of the model.