Metaheuristics in the Age of AI and Big Data: A Decade of Progress and Future Outlook

Abstract

Metaheuristics are important tools for solving complex problems in computer science, especially in areas like artificial intelligence (AI), big data, and network optimization. This paper looks at how these techniques have developed from 2010 to 2023, focusing on recent trends, applications, and new ideas. We discuss the strengths and weaknesses of metaheuristics, along with the challenges they face. For example, while they are flexible and can be applied to many problems, they often require a lot of computational power and can be difficult to fine-tune. Despite these challenges, there is still much potential for improvement. We suggest areas for future research that could make metaheuristics even more effective. By understanding these trends and challenges, researchers and practitioners can create better solutions in their fields.