Social networks, personal blog pages, on-line transaction web-sites, expertise web pages and location based social networks provide an attractive platform for millions of users to share opinions, comments, ratings, etc. Having this kind of diverse and comprehensive information leads to difficulties for users to reach the most appropriate and reliable conclusions. Recommendation systems form one of the solutions to deal with the information overload problem by providing personalized services. Using spatial, temporal and social information on recommender systems is a recent trend that increases the performance. Also, taking into account more than one criterion can improve the performance of the recommender systems. In this paper, a location and social network aware recommender system enhanced with multi objective filtering is proposed and described. The results show that the proposed method reaches high coverage while preserving precision. Besides, the proposed method is not affected by the range of ratings and provides persistent results in different settings.