Sizing truss structures using teaching-learning-based optimization

Meta-heuristic search methods have been extensively used for optimization of truss structures over the past two decades. In this study, a new meta-heuristic search method called ‘teaching-learning-based optimization’ (TLBO) is applied for optimization of truss structures. The method makes use of the analogy between the learning process of learners and searching for designs to optimization problems. The TLBO consists of two phases: teacher phase and learner phase. ‘Teacher phase’ means learning from the teacher and ‘learner phase’ means learning by the interaction between learners. The validity of the method is demonstrated by the four design examples. Results obtained for the design examples revealed that although the TLBO developed slightly heavier designs than the other meta-heuristic methods in a few cases, it obtained results as good as or better than the other meta-heuristic optimization methods in terms of both the optimum solutions and the convergence capability in most cases.

► Teaching-learning-based optimization method is developed for sizing optimization of truss structures.
► The sensitivity analysis for the best combination of tuning parameters is performed.
► The increase of ndlp resulted in the decrease in the number of structural analyses.