论文标题
自然风格的优化算法：挑战和开放问题
Nature-Inspired Optimization Algorithms: Challenges and Open Problems
论文作者
论文摘要
科学和工程中的许多问题可以作为优化问题提出，但要受复杂的非线性约束。高度非线性问题的解决方案通常需要复杂的优化算法，并且传统算法可能难以解决此类问题。当前的趋势是由于其灵活性和有效性而使用自然风格的算法。但是，关于自然风格的计算和群智能存在一些关键问题。本文对一些最新的自然风格算法进行了深入的评论，重点是他们的搜索机制和数学基础。确定了一些具有挑战性的问题，并突出了五个开放问题，这些问题是关于算法收敛和稳定性，参数调整，数学框架，基准测试和可扩展性的作用的分析。这些问题与未来研究的方向讨论。
Many problems in science and engineering can be formulated as optimization problems, subject to complex nonlinear constraints. The solutions of highly nonlinear problems usually require sophisticated optimization algorithms, and traditional algorithms may struggle to deal with such problems. A current trend is to use nature-inspired algorithms due to their flexibility and effectiveness. However, there are some key issues concerning nature-inspired computation and swarm intelligence. This paper provides an in-depth review of some recent nature-inspired algorithms with the emphasis on their search mechanisms and mathematical foundations. Some challenging issues are identified and five open problems are highlighted, concerning the analysis of algorithmic convergence and stability, parameter tuning, mathematical framework, role of benchmarking and scalability. These problems are discussed with the directions for future research.
