Analysis and Enhancement of Simulated Binary Crossover

Most recombination operators are designed with the aim of altering its exploration capabilities depending on the distance between the parents involved in the process. However, relating the exploration capability of crossover operators only to the distance between parents might be a drawback in long-term executions because diversity could not be large enough after some generations, so the search process might stagnate. This paper proposes some extensions of the Simulated Binary Crossover (SBX) to generate dynamic variants of SBX (DSBX). The dynamic variants consider the stopping criterion to alter their internal operation. The main objective of the extensions is to induce a gradual change from exploration to intensification in the search process, which is performed by dynamically altering three different features of the original SBX. In order to validate the effectiveness of our proposal DSBX is integrated in three different state-of-the-art Multi-objective Evolutionary Algorithms (MOEAs). The experimental validation performed with the popular DTLZ, WFG and UF benchmarks shows a significant improvement of all the MOEAs when applying the novel crossover operator. Additionally, our proposal is also tested against schemes that incorporate differential evolution operators, showing quite competitive results.