DHEARENDRA GARG, Dr. Ashutosh Dwivedi
Optimization, TLBO (Teaching–Learning–Based Optimization), MATLAB, mechanically constrained
A new efficient optimization method for mechanical design optimization is developed in this paper, TLBO (Teaching–Learning–Based Optimization). Focuses on how a teacher's influence on pupils. The TLBO algorithm follows in the footsteps of other algorithms inspired by nature and based on populations of solutions to arrive at a global solution. The population refers to all the pupils in a certain class. As part of the TLBO technique, there are two phases: one for the teacher and one for the learner. The "Teacher Phase" and "Learner Phase" are two separate stages of learning. All the TLBO method's basic ideas are laid out in detail. The approach's efficacy is investigated using five separate limited benchmark test functions, four distinct benchmark mechanical design difficulties, and six real-world optimization issues. Efficiencies such as best solution, average solution, convergence rate and computational effort are all considered when comparing it to other population-based optimization techniques. It is presented in this paper that TLBO was more effective than other optimization methods in tackling the mechanical design optimization difficulties under investigation. Engineers may be able to use this new method of optimization to solve additional optimization problems. For the optimization problem, MATLAB code is utilized to provide an optimized strategy for teaching and learning based on an evolutionary algorithm that simulates the teaching– learning phenomena that occur in classrooms. The mechanically constrained design (TLBO) method is investigated in this work, which studies analysis methods.
Article Details
Unique Paper ID: 162306

Publication Volume & Issue: Volume 10, Issue 9

Page(s): 140 - 149
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