A comparative study of DE, PSO and BFO for optimisation of rectangular Microstrip patch antenna with inset feed parameter

Achieving high gain resonating antenna at a prerequisite frequency is a real time problem. A Microstrip patch antenna is highly dependent on its designing. Although theoretically it is possible to find out the parameters for a particular frequency, the outcome is not always accurate. Since this process of combining sets of parameters is time consuming, using optimization algorithms seems a plausible option. Differential Evolution uses real parameters and uses the difference in the vectors to scan the contours of the fitness function. The function used to find the minima is the impedance function as a resonance is obtained when the impedance of antenna matches the input impedance. Unlike DE, Particle swarm optimization defines a set of locations and velocities of the members of vector array, using parallel search techniques starting with many vectors from initial position and communicating amongst themselves to find the global optima. On the other hand, Bacterial Foraging Optimization algorithm, despite being a swarm based algorithm, uses a different approach imitating the behavior of a bacteria at different situations. Although each algorithm is fed with the exact same parameters, the outcomes are strikingly different. Each algorithm optimizes the problem of resonating patch in its own way and time.