Treffer: An Intelligent Soft Computing-Oriented Strategy for Managing Global Sustainability Issues in Dynamic Environments.

Global sustainability has emerged as one of the most pressing challenges of the twenty-first century, encompassing critical environmental, social, and economic dimensions. Issues such as climate change, resource scarcity, population growth, and rapid urbanization are creating increasingly complex systems that require innovative and adaptive solutions. Traditional computational approaches often fail to capture the uncertainty, ambiguity, and dynamism of sustainability challenges at the global scale. In this context, intelligent soft computing has become a powerful paradigm capable of managing complexity, handling imprecision, and supporting multi-criteria decision-making. This paper proposes an intelligent soft computing-oriented strategy for managing global sustainability issues in dynamic environments. By integrating fuzzy logic, neural networks, evolutionary computation, and hybrid intelligent systems, the proposed framework can adapt to evolving conditions and provide policymakers with robust insights. The study highlights applications across renewable energy systems, smart cities, sustainable agriculture, and climate policy modeling. Furthermore, it critically evaluates the limitations of soft computing approaches and outlines future research directions. The findings emphasize the potential of intelligent soft computing as a holistic and adaptive strategy that can support sustainable development goals (SDGs) and provide decision-makers with flexible tools for navigating uncertainty in complex global systems. [ABSTRACT FROM AUTHOR]