# Comparative Study of Sound Transmission Losses of Sandwich Composite Double Panel Walls
## 5 Parameter Effects and Optimization Strategy on the Sound Transmission Loss of Double Panel Walls
### Optimization of Sound Transmission Loss of Double Panel Structures

Table 2: Summary of selected studies of parameter effects on STL of sandwich and composite double panel structures. has been a veritable method used by researchers to produce better performance of structures [151; 152]. The optimization problem generally involves, for example,  
finding the design vector \(x\)  
that minimizes the objective function \(f(x)\)  
subject to: constraint 1 (_inequality_), constraint 2 (_equality_)  
To maximize the objective function, for instance, the STL, the minimized objective function can be negated. Optimization techniques can be applied, therefore, on these structures to maximize their STL and reduce their weight as demonstrated by [PERSON] et al. [153] who used a genetic algorithm approach. Contemporary researchers have adopted the multi-objective optimization problem which involves the solution of a number of parameters capable of minimizing the objective functions and satisfying the sets of defined restrictions, or constraints. Solving a multi-objective optimization problem give rise to what is known as Pareto optimal solution. These are non-dominated vectors on the Pareto optimal set when the objective functions are plotted. In other words, at least one of the objective values must be degraded before the solutions can be improved in any of the objective functions. An optimization problem of panels with multiple layers and multi-objective criteria was undertaken by [PERSON] et al. [154]. The combination of the genetic algorithm and the transfer matrix method was adopted by the authors to obtain the best solutions of the problem. In recent times, [PERSON] et al. [34] combined both the non-dominated sorting genetic algorithm and the first order deformation theory to obtain the optimal solutions of the STL of composite cylindrical shell with porous materials. Their optimization involved the use of first cost function to minimize the weight; and a second cost function was minimized to maximize the STL. Moreover, in their optimization procedure, two points were selected such that the first had a maximum STL and the second had a minimum weight of the Pareto front. The design variables were ply orientation, composite material types and porous material types. The optimized results due to ply orientation were compared with the non-optimized ones. Their results showed an increase in the STL for the two optimal points compared to the non-optimum one, in all frequency regions. A bi-optimization problem that involved maximizing the transmission loss and minimizing the weight was also carried out by [PERSON] et al. [155] and they obtained the Pareto fronts. In their result, the transmission loss increased at the expense of increased weight below the limit value of the Pareto front while above this front, the transmission loss decreased. One of the advantages of carrying out this bi-optimization problem by the authors is that it helped to distinguish the acoustic superiority of different structures. Optimization problems especially in the low frequency range have also been carried out by [PERSON] and [PERSON] [45] and [PERSON] and [PERSON] [156]. Core optimization of sandwich DPS in a wide frequency range has also been performed by [157]. Finally, [PERSON] et al. [158] adopted a conjugate gradient optimization technique to calculate and optimize the material properties on the STL of composite plate.