Directional crossover hunger games search with adaptive Lévy diversity for network subculture

In this paper, we explore and analyze the network subculture in the youth and actively explore the new path of socialist core values to cultivate the values of college students. Through the effective questionnaire survey of college students, the prediction model of decision support is established by improving the metaheuristic algorithms. Hunger games search (HGS) is a metaheuristic algorithm widely used in many fields. However, the method converges slowly and veers toward the local optimum when presented with challenging problems. Therefore, there is room for HGS to develop. We introduce a brand-new HGS variant, denoted as SDHGS. This variant combines the directional crossover mechanism with an adaptive Lévy diversity strategy. The directed crossover mechanism endeavors to harmonize the interplay between exploration and exploitation, while the adaptive Lévy diversity facet enhances the range of variations within the population. The cooperation of these mechanisms within SDHGS concludes in an augmented convergence rate and heightened precision. SDHGS is compared to HGS, seven classic algorithms, and enhanced algorithms on the benchmark function set to evaluate and demonstrate the performance. Besides, various analytical techniques, such as the Friedman test and the Wilcoxon signed-rank test, are considered when analyzing the experimental results. The findings demonstrate that SDHGS with two techniques greatly enhances HGS performance. Finally, SDHGS is applied to discuss the internal relationship that affects the existence of youth subculture and establish a prediction model of decision support.