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Jamming technology for satellite navigation has been widely used in some fields. The distributed jamming system contains a large number of jamming sources. How to schedule the limited resources efficiently to fully utilize their operational effectiveness is important in distributed jamming for satellite navigation. Most of the existing studies about jamming for satellite navigation only pay attention to the jamming benefits, ignoring the jamming cost. We introduce the concept of jamming cost for satellite navigation. Firstly, we propose a method to evaluate jamming benefit for satellite navigation based on the principle of navigation signal processing of the receiver. Secondly, we analyze the overall benefit and cost of jamming resource scheduling countermeasures in two different scenarios for satellite navigation. Then we establish two multi-constrained resource scheduling model that maximizes jamming benefit and minimizes jamming cost. The particle swarm optimization (PSO) and the genetic algorithm (GA) are applied to solve the problem. Simulation results show that the performance of GA and PSO is better than traditional Simulated Annealing (SA) in two different scenarios. In both "one-to-one" and "many-to-one" scenarios, the GA can achieve better objective value but with a little longer time than the SA. While the PSO finds a little better objective value with shorter time than the SA. In conclusion, the GA is not easier to fall into local optimal solution. And the solution speed of the PSO is faster than the SA.