A self-adaptive variant of teaching–learning-based optimization, incorporating a diversity archive and referred to as ATLBO-DA, has been proposed. Combined with a new path repairing technique (PRT), it efficiently accomplishes the four-bar linkage path generation problem, but an upgraded version is needed. An update of ATLBO-DA to self-adaptive teaching–learning-based optimization with evenness factor archive (ATLBO-EFA) and a new path repairing technique are proposed at the present. The diversity archive idea of the original version is replaced with the evenness factor archive to increase the exploitation and exploration performance of the TLBO. An optimum path repairing technique (OPRT) is proposed. This novel approach is used to identify the optimum combination of four-bar mechanism types by employing the concept of Degree of Limiting (DL). Moreover, in this article, a comparative analysis of present update and the previous version use to solve four-bar linkage path generation problems is performed. Several path generation problems are solved using both techniques. The results demonstrate that the updated technique consistently outperforms the earlier version, giving superior values for both mean and minimum descriptive statistics. In addition, the results make it clear that ATLBO-EFA and OPRT are superior to the original version. The result of non-parametric statistic testing using Friedman test indicate that ATLBO-EFA ranks 1st at p-value (0.0455) < α (0.05). It can be concluded that ATLBO-EFA with OPRT offers the best solution for solving the four-bar path synthesis problems.
Winyangkul et al. (Sat,) studied this question.