3.1.1. Chaotic EHO

Tuba et al. [106] proposed a new EHO algorithm with chaos theory called CEHO to solve unconstrained global optimization problems. In CEHO, two different chaotic maps are introduced into the EHO algorithm. Compared with 15 standard benchmark functions from IEEE Congress on Evolutionary Computation (CEC) 2013, the CEHO algorithm outperforms the basic EHO and PSO in almost all cases.


**Table 1.** The improved EHO algorithms.

**Figure 4.** Different variants of EHO.

3.1.2. EHO with Individual Updating Strategies

Li et al. [107] incorporated six individual updating strategies into basic EHO. The experimental results for sixteen test functions show that the proposed improved EHO variant significantly outperformed basic EHO.

#### 3.1.3. <sup>L</sup>évy Flight EHO

Xu et al. [108] applied an improved EHO algorithm with <sup>L</sup>évy flight (LFEHO) to solve network intrusion detection problems. The research results showed that the LFEHO algorithm increased the accuracy rate of the network.

Xu et al. [109] proposed improved EHO (IEHO) to solve network intrusion detection problems, which improved the classification performance of intrusion detection under the premise of ensuring the accuracy rate and meeting the needs in real time. The experimental results showed that the IEHO algorithm was superior to other algorithms (EHO [105], PSO [2], and MS [77]).
