Drawing inspiration from the philosophy of Yi Jing, the Yin-Yang pair optimization (YYPO) algorithm has been shown to achieve competitive performance in single objective optimizations, in addition to the advantage of low time complexity when compared to other population-based meta-heuristics. Building upon a reversal concept in Yi Jing, we propose the novel Yi optimization (YI) algorithm. Specifically, we enhance the Yin-Yang pair in YYPO with a proposed Yi-point, in which we use Cauchy flight to update the solution, by implementing both the harmony and reversal concept of Yi Jing. The proposed Yi-point balances both the effort of exploration and exploitation in the optimization process. To examine YI, we use the IEEE CEC 2017 benchmarks and compare YI against the dynamical YYPO, CV1.0 optimizer, and four classical optimizers, i.e., the differential evolution, the genetic algorithm, the particle swarm optimization, and the simulated annealing. According to the experimental results, YI shows highly competitive performance while keeping the low time complexity. The results of this work have implications for enhancing a meta-heuristic optimizer using the philosophy of Yi Jing. While this work implements only certain aspects of Yi Jing, we envisage enhanced performance by incorporating other aspects.

翻译：受《易经》哲学启发，阴阳对优化（YYPO）算法在单目标优化中展现出具有竞争力的性能，且与其他基于种群的元启发式算法相比具有时间复杂度低的优势。基于《易经》中的“变易”思想，我们提出了一种新颖的易优化（YI）算法。具体而言，我们通过引入所提出的易点来增强YYPO中的阴阳对，其中我们运用柯西飞行来更新解，同时实现了《易经》的“和谐”与“变易”概念。所提出的易点在优化过程中平衡了探索与开发的努力。为检验YI算法，我们采用IEEE CEC 2017基准测试集，并将YI与动态YYPO、CV1.0优化器以及四种经典优化器（即差分进化、遗传算法、粒子群优化和模拟退火）进行比较。实验结果表明，YI在保持低时间复杂度的同时，表现出高度竞争力的性能。本工作的结果对利用《易经》哲学增强元启发式优化器具有启示意义。尽管本工作仅实现了《易经》的某些方面，我们预期通过融入其他方面可进一步提升算法性能。