Drawing inspiration from the philosophy of Yi Jing, Yin-Yang pair optimization (YYPO) has been shown to achieve competitive performance in single objective optimizations. Besides, it has the advantage of low time complexity when comparing to other population-based optimization. As a conceptual extension of YYPO, we proposed the novel Yi optimization (YI) algorithm as one of the best non-population-based optimizer. Incorporating both the harmony and reversal concept of Yi Jing, we replace the Yin-Yang pair with a Yi-point, in which we utilize the Levy flight to update the solution and balance both the effort of the exploration and the exploitation in the optimization process. As a conceptual prototype, we examine YI with IEEE CEC 2017 benchmark and compare its performance with a Levy flight-based optimizer CV1.0, the state-of-the-art dynamical Yin-Yang pair optimization in YYPO family and a few classical optimizers. According to the experimental results, YI shows highly competitive performance while keeping the low time complexity. Hence, the results of this work have implications for enhancing meta-heuristic optimizer using the philosophy of Yi Jing, which deserves research attention.

翻译：根据Yi Jing的理念,Yin-Yang对口优化(YYPO)被证明能够在单一目标优化中实现竞争性业绩。此外,与其他基于人口的优化相比,它具有低时间复杂性的优势。作为YYPO的概念延伸,我们提议将新颖Yi优化算法作为最佳非基于人口的优化方法之一。纳入Yi Jing的和谐和反向概念,我们用Yi点取代Yin-Yang对口,我们利用Levy飞行更新解决方案,平衡探索和优化过程中的利用。因此,作为概念原型,我们用IEEE CEC 2017基准来审查YII,并将其业绩与Levy飞行优化标准CV1.0(YPO家庭最先进的Yin-Yang动态对口优化和一些经典优化)。根据实验结果,YI显示高竞争力的业绩,同时保持低时间复杂性。因此,这项工作的结果对利用Yi J的哲学研究加强元经济最优化的影响,值得关注。