This study introduces a novel multi-objective optimization algorithm
integrating Customized Mutated PSO (CM-PSO) and an innovative modified
Genetic Algorithm (GA) using an unexplored merged chaotic map. The
hybrid algorithm con- verges to desired results faster than CM-PSO and
modified GA without trapping in local minima. Validation is conducted by
designing a single-element and simple-structure dipole antenna so that
its optimized S 11 is better than -30 dB at the resonance frequency and
covers the 3.3 to 3.8 GHz fre- quency band with S 11 < − 1 0
dB. Certainly, the -30 dB and covering frequency band criteria can be
modified in the pro- posed algorithm. In the algorithm, the isolation
between el- ements of a quad-Multiple-Input/Multiple-Output antenna,
constructed using optimized dipole antennas, is set to be less than -20
dB (changeable criteria) so that the smallest size can be achieved. CST
carries out electromagnetic and high- frequency simulations, and the
novel developed optimization algorithm in MATLAB determines what and how
much pa- rameter values need to be changed by CM-PSO or an innova- tive
modified GA in order to enhance the antenna’s S 11 result and its
Impedance Bandwidth (IBW). The input parameters of the algorithm are the
dimensions of the proposed antenna’s elements, which significantly
influence its performance.