Electromagnetic cloak design with mono-objective and bi-objective optimizers: seeking the best tradeoff between protection and invisibility

TL;DR

This paper introduces novel mono-objective and bi-objective optimization algorithms for electromagnetic cloak design, aiming to optimize protection and invisibility without geometric transformations, using a ternary grey wolf algorithm and a genetic algorithm.

Contribution

It presents a new ternary grey wolf optimization algorithm and adapts a bi-objective genetic algorithm for electromagnetic cloak design, focusing on tradeoffs between protection and invisibility.

Findings

The ternary grey wolf algorithm effectively searches permittivity space.

The bi-objective genetic algorithm identifies optimal protection-invisibility pairs.

The methods improve cloak performance without geometric transformations.

Abstract

We revisit the design of cloaks, without resorting to any geometric transform. Cancellation techniques and anomalous resonances have been applied for this purpose. Instead of a deductive reasoning, we propose a novel mono-objective optimization algorithm, namely a ternary grey wolf algorithm, and we adapt a bi-objective optimization algorithm. Firstly, the proposed chaotic ternary grey wolf algorithm searches three-valued spaces for all permittivity values in the cloak while minimizing the summation of a protection criterion and an invisibility criterion. Secondly, a bi-objective genetic algorithm is adapted to find pairs of optimal values of invisibility and protection.