Network-on-Chip (NoC) is a growing and promising communication para- digm for Multiprocessor-System-On-Chip (MPSoC) design, because of its scalability and performance features. In designing such systems, mapping and scheduling are be- coming critical stages, because of the increase of both size of the network and appli- cation's complexity. Some reported solutions solve each issue independently. However, a conjoint approach for solving mapping and scheduling allows to take into account both computation and communication objectives simultaneously. This paper shows a mapping and scheduling solution, which is based on a Population-Based Incremental Learning (PBIL) algorithm. The simulation results suggest that our PBIL approach is able to find optimal mapping and scheduling, in a multi-objective fashion. A 2-D heterogeneous mesh was used as target architecture for implementation, although the PBIL representation is suited to deal with more complex architectures, such as 3-D meshes.