Chapter 10: Selected Topics and Practical Issues

As demonstrated in Chapter 9, surrogate-assisted algorithms of Chapters 7 and 8 can be utilized for expedited multi-objective optimization of antenna structures. The same methods can also handle expensive computational models in other engineering disciplines (cf. Chapter 11). Here, we discuss several aspects and practical issues of these techniques. In particular, we look into their scalability properties. More specifically, we are interested in the relationship between dimensionality of the design space and the computational cost of the optimization algorithm (Sec. 10.1). Another issue is statistical analysis of surrogate-assisted multi-objective optimization algorithm of Sec. 7.1, where several components are of stochastic nature. In particular, the initial Pareto front approximation is obtained using multi-objective evolutionary algorithm (MOEA). In Sec. 10.2, we investigate the influence of MOEA operation on the quality of the final Pareto set representation found by the optimization procedure. Finally, in Sec. 10.3, we study the effect of various patch size setups on the cost and performance of sequential domain patching (SDP) algorithm of Sec. 7.3. The studies presented in this chapter lead to certain conclusions concerning the robustness of the considered optimization procedures, indicate potential applicability for solving more challenging problems (than those presented so far in the book), as well as give some guidelines and recommendations in terms of the algorithm setup.