Abstract: The aim of present study is to introduce a heuristic optimization method which is inspired from competitions in social behaviors. Competitive behaviors could be observed in large number of situations of human social life. Particularly we propose a global optimization algorithm which is stochastic, iterative and population-based like genetic algorithms and particle swarm optimization. In this method, the intra and inter group competitions among parties in a parliament, trying to take the control of the parliament are simulated. Performance of this method for function optimization over some benchmark multi-dimensional functions, of which global and local minimums are known, is compared with traditional genetic algorithms.