## 5 Results
### Countries  
Some countries and regions are driving innovation in the field of hyper-heuristics. Figure 7 visually represents the geographical distribution of hyper-heuristic research activity. The color intensity of each country reflects its relative contribution to the field, as measured by the number of published documents. While China currently holds a dominant position, the presence of other nations suggests a competitive research landscape. Figure 8 illustrates the top 10 countries based on the number of publications on hyper-heuristics. The graph highlights the global nature of hyper-heuristic research, with contributions from a diverse range of countries. Figure 6: The top 10 journals regarding production and citations. Figure 7: Countries’ productivity map. Figures 7 and 8 show that China has the largest number of publications, indicating a strong research presence and active engagement in hyper-heuristic research. China's substantial lead in hyper-heuristic publications is likely due to a combination of factors, including significant national investment in science and technology, a large and growing research community, and a strong emphasis on applied research and technological advancement in areas like AI [56]. The scale and complexity of problems in China's rapidly developing economy and collaborative research environment may also contribute to this high volume of publications. The United Kingdom's strong standing as the second-leading country in hyper-heuristic publications is likely due to its robust academic foundation in optimization and operations research, with numerous prestigious universities and research institutions actively involved in this field [57]. The UK's research community demonstrates a balanced approach, focusing on both the theoretical underpinnings and practical applications of hyper-heuristics. This active and well-supported research environment, with historical strengths in related areas like metaheuristics, contributes significantly to the high publication output in hyper-heuristics. On the other hand, India, Spain, and Mexico follow the United Kingdom, demonstrating significant contributions from Western and developing nations. Brazil, Malaysia, Australia, Iran, and Turkey also have a notable presence in the field, suggesting growing interest and research activity in these regions. Figure 9 presents a Sankey diagram that illustrates the flow of research publications from various journals to different countries, with each country focusing on specific keywords related to hyper-heuristics. The thickness of the flows represents the relative volume of publications. According to Figure 9, the UK's research concentrates on optimization, connecting to _Evolutionary Computation_ and the _European Journal of Operational Research_. Chinese and New Zealand's research is primarily focused on genetic programming. China also has significant links to optimization and reinforcement learning. Optimization, a fundamental principle in hyper-heuristics, is a common thread connecting diverse research areas across the United Kingdom and China. Meanwhile, China's emphasis on genetic programming highlights its potential as a promising approach for addressing complex optimization challenges. Lastly, China's focus on reinforcement learning underscores its growing importance in the field, particularly for dynamic and complex problems. Figure 8: Top 10 countries in terms of number of publications. Figure 9 reveals that, while there are regional differences in research emphasis, optimization remains a central theme across all three countries. The decisive role of Q-learning and reinforcement learning highlights the underlying principle of hyper-heuristics as a way of machine learning. Figure 9 also demonstrates overlapping areas of interest among different countries, suggesting potential for international collaborations. Figure 9 further illustrates these collaborative relationships between authors from various countries.