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.