This paper will investigate a method of synthesizing planar arrays through the application of a new optimization algorithm based on competitive behavior of animal groups that will impose deeper nulls in the interfering direction with the constraint of a reduced Side Lobe Level (SLL). Simulation results for optimal patterns by position-only and both the element space and amplitude controlling with the imposed single and double nulls are given to show the effectiveness of the proposed method. In the following, after a general explanation of the algorithm, a comparison of obtained results with particle swarm optimizations, as a well-known heuristic algorithm, is presented. Furthermore, in order to set which design case could provide a better performance in imposed deeper nulls and side lobe reduction, a comparative evaluation of both proposed methods (position-only, position and amplitude) will be done. Finally, the optimized design case with a uniform planar array will be achieved. Also, the proposed algorithm on array antenna synthesis, shows faster and superior results compared to other optimization algorithms.