Teaching-Learning-Based Optimization Algorithm for Pressure Vessel Design Problem - Hawar Bahzad Ahmad; Danial William Odeesho; Reving Masoud Abdulhakeem; Merdin Shamal Salih; Zebari, Dilovan (The Indonesian Journal of Computer Science, 2025)
This paper presents the utilization of the Teaching-Learning-Based Optimization (TLBO) algorithm to tackle the intricate problem of pressure vessel design. Design optimization for pressure vessels holds a critical role in various engineering domains, demanding effective techniques for achieving designs that are both optimal and safe. The TLBO algorithm, drawing inspiration from the dynamics of teaching and learning, offers a unique approach by amalgamating exploration and exploitation strategies. In this research, we investigate the incorporation of TLBO within the realm of pressure vessel design, with the objective of improving design efficiency while strictly adhering to demanding safety and performance benchmarks. Through a comprehensive assessment, we analyze the performance of TLBO in generating optimal designs and draw comparisons with established optimization methods. Our findings underscore the proficiency of TLBO in effectively converging towards competitive solutions, thus highlighting its potential to bring about a paradigm shift in the domain of pressure vessel design optimization. This paper underscores the importance of the Teaching-Learning-Based Optimization algorithm as a transformative instrument, providing invaluable insights for researchers, practitioners, and experts involved in fields such as structural engineering, optimization, and related disciplines.