The recombination of genetic material to be inherited by the offspring is achieved with the simulated binary crossover (SBX) operator, which is a real-valued analogue of the single-point crossover of binary strings that were used in early GAs with discrete degrees of freedom. This simple operator cuts and swaps at one random site in the bit representations. More specifically, SBX is designed to enhance the probability for two parents to give birth to an arbitrary child solution and better explore the fitness landscape. More details about the SBX implementation are provided in Appendix 6.1. This operator demonstrated better performance in finding global optima of multi-variable objective functions with numerous LM. To illustrate its enhanced search power, we report the number of LM visited along a GA run with SBX in Figure , compared to simple swaps of Θ components (genewise crossover ) that covers less space on average.