According to the properties of outdoor advertising, a pricing strategy model was proposed based on location based service and big data. It was modeled as a constrained integer optimization model to maximize the total revenue of operators. An improved particle swarm optimization was proposed for solving the outdoor advertising optimization problem, using the penalty function method for constraint handling. The simulation results show the validity of the algorithm. Applying this model to outdoor advertising for comprehensive pricing can better solve the common interests of advertisers and relevant advertising operators, and maximize the interests of both parties.