The papers in this special section focus on smart fuzzy optimization in operational research and renewable energy. Over the last five decades, fuzzy optimization has found numerous successful applications in diverse fields, including operational research (OR), manufacturing, information technology, energy optimization, data science, smart cities, and big data analytics. Fuzzy optimization has strongly influenced research and development into other areas of intelligent computing leading to many hybrid and deep learning systems. It has opened new horizons in thinking, research and development and it will guide us into another half century of progress. In actually, fuzzy optimization is an approximation of nonlinear optimization, which has formed a systematic but not yet unified theory of fuzzy systems and other fuzzy-set based methodologies. Fuzzy optimization along with decision making is an interdisciplinary area, which focuses on extracting useful knowledge with data technology and employing it. Specific topics include fuzzy sets, rough sets, statistical methods, parallel/distributed data mining, hybrid fuzzy optimization, hybrid evolutionary and swarm intelligence methods, big data optimization, IoTs, flexibility, reliability and robustness, smart systems, high-dimensional and big-data analytics, energy optimization, and software engineering.

中文翻译：

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客座社论：运筹学和可再生能源中的智能模糊优化：建模，仿真和应用

本节的论文重点在于运筹学和可再生能源中的智能模糊优化。在过去的五十年中，模糊优化已在各个领域获得了许多成功的应用，包括运筹学（OR），制造，信息技术，能源优化，数据科学，智慧城市和大数据分析。模糊优化已极大地影响了智能计算其他领域的研发，从而导致了许多混合和深度学习系统。它为思想，研究和发展开辟了新的视野，它将引导我们进入另一个半个世纪的进步。实际上，模糊优化是非线性优化的近似，它已经形成了系统的但尚未统一的模糊系统理论和其他基于模糊集的方法。模糊优化与决策一起是一个跨学科领域，其重点是利用数据技术提取有用的知识并加以利用。具体主题包括模糊集，粗糙集，统计方法，并行/分布式数据挖掘，混合模糊优化，混合进化和群体智能方法，大数据优化，IoT，灵活性，可靠性和鲁棒性，智能系统，高维和大数据数据分析，能源优化和软件工程。