Multi-objective optimization of heat exchangers using a modified teaching-learning-based optimization algorithm
R. Venkata Rao,Vivek Patel +1 more
TLDR
In this paper, a modified version of the TLBO algorithm is introduced and applied for the multi-objective optimization of heat exchangers, where the objective function is to maximize the heat exchanger effectiveness and minimize the total cost of the exchanger.About:
This article is published in Applied Mathematical Modelling.The article was published on 2013-02-01 and is currently open access. It has received 305 citations till now. The article focuses on the topics: Plate fin heat exchanger & Shell and tube heat exchanger.read more
Citations
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Proceedings ArticleDOI
Teaching-Learning Based Optimization Algorithm Based on Course by Course Improvement
TL;DR: The results of four classic test functions show that the TLBOCI algorithm could outperform TLBO in quality of solutions and convergence speed under the condition of not introducing new parameters thus keeping the simplicity of TLBO.
Journal ArticleDOI
Optimization Techniques for Engineering Design
TL;DR: This paper discusses the popular evolutionary optimization technique, Genetic Algorithm (GA) and Teaching-learningbased Optimization (TLBO) algorithm and the definitions of various parameters used by these algorithms.
Book ChapterDOI
Design Optimization of Plate-Fin Heat Exchanger Using Sine Cosine Algorithm
TL;DR: A recent proposed meta-heuristic algorithm named sine cosine algorithm (SCA) is adopted to solve the problem of the design and optimization of the PFHE and compared with the results of several classical and new algorithms.
Journal ArticleDOI
Optimal approximation of linear systems using a Teaching-Learning-Based Optimization algorithm
TL;DR: Experimental results show that the proposed Teaching-Learning-Based Optimization can effectively approximate stable and unstable linear systems.
Book ChapterDOI
Thermal Design and Optimization of Heat Exchangers
TL;DR: In this paper, thermal modeling of different types of heat exchangers, such as shell and tube heat exchanger, plate-fin heat exchange, fin-and-tube heat exchange and rotary regenerator, is presented.
References
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Journal ArticleDOI
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.
Journal ArticleDOI
Compact heat exchangers
TL;DR: The third edition of the second edition as discussed by the authors was published in 1964 and contains basic test data for eleven new surface configurations, including some of the very compact ceramic matrices, in both the English and the Systeme International (SI) system of units.
Journal ArticleDOI
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.
Journal ArticleDOI
An elitist teaching-learning-based optimization algorithm for solving complex constrained optimization problems
R. Rao,Vivek Patel +1 more
TL;DR: Elitism concept is introduced in the TLBO algorithm and its effect on the performance of the algorithm is investigated and the effects of common controlling parameters such as the population size and the number of generations on the results are investigated.
Journal ArticleDOI
Heat exchanger design based on economic optimisation
TL;DR: In this paper, a procedure for optimal design of shell and tube heat exchangers is proposed, which utilizes a genetic algorithm to minimize the total cost of the equipment including capital investment and the sum of discounted annual energy expenditures related to pumping.
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R. Rao,Vivek Patel +1 more