Constraint handling technique for four-bar linkage path generation using self-adaptive teaching–learning-based optimization with a diversity archive

Abstract

This article proposes an alternative constraint handling technique for the four-bar linkage path generation problem. The constraint handling technique that is traditionally applied uses an exterior penalty function, and has been found to be inefficient, particularly when dealing with constraints on the input angles. The new technique deals with both input crank rotation and Grashof's criterion. Four classical path generation problems are used to test the performance of the proposed technique. A new adaptive teaching–learning-based optimization (TLBO) scheme is used to solve several optimization problems. This technique is referred to here as teaching–learning-based optimization with a diversity archive (ATLBO-DA), and was specifically developed for this design problem. The results show that this new design concept gives better results than those of previous work, and that ATLBO-DA is superior to the original version and other metaheuristic algorithms.