An interesting approach to the topological optimization of the engine mount of a transport aircraft, based on genetic algorithms, is presented in this paper. Sections 2 through 5 discuss the problem definition, the topological design variables, the geometric properties of the system, and the chosen objective function. The last two sections present, in depth, the optimization procedure, the bit masking-oriented genetic algorithm, and computational results. The objective function to be minimized is the structural weight, which is equivalent (assuming constant density) to minimizing structural volume. The constraints model both static and dynamic requirements.

Of particular interest is section 6, where the bit masking-oriented genetic algorithm is discussed in detail. Here, the authors prove that the various specialized algorithms used to define genetic operators (such as mutation and crossover) can be replaced by Boolean vector functions. They demonstrate how the mask vector could be defined for the widely used cut-crossover, bit-by-bit crossover, and local cut-crossover. Moreover, they propose some interesting extensions (section 6.2).

The computational results show a higher convergence rate for the newly proposed genetic algorithm in comparison to the standard one (this is much more visible in the initial phase). The paper is well written, and could be read both by scientists with interests in aircraft design, and by optimization professionals.