On the Design and Reliability Analysis of Electromagnetic Absorbers Using Real-Coded Genetic Algorithm and Monte Carlo Simulation

Abstract

Abstract-In this paper, we propose an approach for designing and quantitatively assessing the performance of the multilayered radarabsorbing structure. In our proposed approach, a five layered radarabsorbing materials design is optimized from the predefined materials database. But to determine the optimal choice of the material and thickness of each layer, a combined binary and real-coded genetic algorithm (GA) is used to handle the integer and real variables involved in such designs. Further, the proposed approach employs the Latin hypercube sampling with Monte Carlo Simulation to carry out the performance based reliability analysis of the design. Absorber synthesized results are compared with the published work using other algorithms. The outcomes of our approach show that the combined GA works quite well, and most prominently the reliability analysis provides the decision maker a means to select among the several design alternatives available before him.

Reliability-based design optimization scheme for designing electromagnetic shielding structures

“…The resulting design solution is provided in Table 3. The accuracy of the evaluated active probabilistic constraints, as shown in Table 3, has been checked by employing Monte Carlo Simulation (MCS) [20] with ten-million sample size at the optimum design. The relative error is calculated as follows:…”

“…Our analysis has shown such variations in the expected SE and absorption using probability distributions of possible variations in the variables and parameters for the deterministic designs of shielding and absorbing structures. [18,20] Therefore, for the realization of reliable optimal shielding structure the uncertainties involved in the decision variables and parameters should be considered in the optimization task. Reliability-based design optimization (RBDO) approaches enable us to optimize the objective subject to prescribed 766…”

An Application of Artificial Intelligence for the Joint Estimation of Amplitude and Two-Dimensional Direction of Arrival of Far Field Sources Using 2-L-Shape Array

“…GA is a more prominent and proficient algorithm than any other evolutionary computing technique due to its ease in conception, ease in implementation, and more importantly less probability to get stuck in the presence of local optima. GA is being successfully applied to a wide range of problems having application in commerce to the leading scientific research [19,20]. The structure of GA exploited for the joint estimation is given in Figure 2.…”

Optimization for Brain Activity Monitoring With Near Infrared Light in a Four-Layered Model of the Human Head

“…It is a very versatile method in solving numerical computing problems [13][14][15]. The principles of the Monte Carlo algorithm based on the variance reduction technique have already been described in [16].…”