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http://dx.doi.org/10.12989/acd.2017.2.4.313

Topology, shape, and size optimization of truss structures using modified teaching-learning based optimization  

Tejani, Ghanshyam G. (Department of Mechanical Engineering, RK University)
Savsani, Vimal J. (Department of Mechanical Engineering, Pandit deendayal petroleum University)
Patel, Vivek K. (Department of Mechanical Engineering, Pandit deendayal petroleum University)
Bureerat, Sujin (Sustainable Infrastructure Research and Development Center, Department of Mechanical Engineering, Khon Kaen University)
Publication Information
Advances in Computational Design / v.2, no.4, 2017 , pp. 313-331 More about this Journal
Abstract
In this study, teaching-learning based optimization (TLBO) is improved by incorporating model of multiple teachers, adaptive teaching factor, self-motivated learning, and learning through tutorial. Modified TLBO (MTLBO) is applied for simultaneous topology, shape, and size optimization of space and planar trusses to study its effectiveness. All the benchmark problems are subjected to stress, displacement, and kinematic stability constraints while design variables are discrete and continuous. Analyses of unacceptable and singular topologies are prohibited by seeing element connectivity through Grubler's criterion and the positive definiteness. Performance of MTLBO is compared to TLBO and state-of-the-art algorithms available in literature, such as a genetic algorithm (GA), improved GA, force method and GA, ant colony optimization, adaptive multi-population differential evolution, a firefly algorithm, group search optimization (GSO), improved GSO, and intelligent garbage can decision-making model evolution algorithm. It is observed that MTLBO has performed better or found nearly the same optimum solutions.
Keywords
meta-heuristic algorithms; truss design; topology; shape; and size optimization; structural optimization;
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