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R.V. Rao
Researcher at Sardar Vallabhbhai National Institute of Technology, Surat
Publications - 5
Citations - 4745
R.V. Rao is an academic researcher from Sardar Vallabhbhai National Institute of Technology, Surat. The author has contributed to research in topics: Particle swarm optimization & Engineering optimization. The author has an hindex of 3, co-authored 5 publications receiving 3483 citations.
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Teaching-learning-based optimization: A novel method for constrained mechanical design optimization problems
TL;DR: The effectiveness of the TLBO method is compared with the other population-based optimization algorithms based on the best solution, average solution, convergence rate and computational effort and results show that TLBO is more effective and efficient than the other optimization methods.
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Teaching-Learning-Based Optimization: An optimization method for continuous non-linear large scale problems
TL;DR: An efficient optimization method called 'Teaching-Learning-Based Optimization (TLBO)' is proposed in this paper for large scale non-linear optimization problems for finding the global solutions.
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Discrete optimisation of a gear train using biogeography based optimisation technique
TL;DR: In this paper, a new global optimisation algorithm, biogeography based optimisation (BBO), for solving discrete optimisation of a gear train is presented, where the objective considered is minimisation of weight.
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Mechanical engineering design optimisation using modified harmony elements algorithm
TL;DR: In this article, a new optimisation algorithm, harmony elements algorithm (HEA), for solving mechanical engineering design optimisation problems is presented, which is inspired by an ancient Chinese philosophy, called as theory of five elements.
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Multi-objective design optimisation of ball bearings using a modified particle swarm optimisation technique
TL;DR: In this article, a modified particle swarm optimisation (PSO) technique was used for the optimization of a ball bearing with three different objectives namely, dynamic capacity, static capacity and elastohydrodynamic minimum film thickness.