Parameter estimation of electromagnetic plane waves is one of the important areas of researchers since few decades. It has got direct applications in the field of radar, sonar, seismic exploration, mobile communication etc. In this dissertation, efficient and new evolutionary algorithms were designed for the parameter estimation of plane waves which include amplitude and direction of arrival. These global search optimization algorithms include Genetic Algorithm, Fractional Order Darwinian Particle Swarm optimization and Flower Pollination Algorithm etc. In order to improve the performance of global search algorithms, these were also hybridized with local search optimization techniques such as Sequential Quartic Programing. Different structures of antenna arrays were used that include uniform linear array, 1L shaped array and 2L shaped arrays for the reception of plane waves of electromagnetic nature. In order to test the validity and reliability of proposed algorithms, mean squared error was used as a fitness evaluation criterion that can be defined as a difference between the actual and estimated responses of the system. In this regard a large number of Monte Carlo simulations were carried out for the statistical analysis in terms of accuracy of estimation, convergence, robustness (against noise) and computational complexity time to validate proposed algorithms. All the simulations were carried out in MATLAB.