Multi-objective optimization of heat exchangers using a modified teaching-learning-based optimization algorithm
R. Venkata Rao,Vivek Patel +1 more
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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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Journal ArticleDOI
Design Analysis of a Helium Xenon-Printed Circuit Heat Exchanger for a Closed Brayton Cycle Microtransport Reactor
TL;DR: In this paper , the effect of geometric structure parameters such as channel diameter, zigzag pitch length, and Zigzag angle on the Nusselt number and Fanning friction factor was investigated using a printed circuit heat exchanger (PCHE) unit model and the principle of least squares was employed to carry out a nonlinear fitting of the flow and heat transfer criterion correlation equations.
Journal ArticleDOI
Multi-Objective Optimization Tool of Shell-and-Tube Heat Exchangers Using a Modified Teaching-Learning-Based Optimization Algorithm and a Compact Bell-Delaware Method
Thomas McCaughtry,Sung in Kim +1 more
TL;DR: The multi-objective optimization of heat exchangers can provide a reliable solution for both improved efficiency and reduction in cost.
Journal ArticleDOI
Neuro-tabu search approach to scheduling in automotive manufacturing
TL;DR: A neuro-tabu algorithm is proposed, which is a variation of the tabu search algorithm with a neural mechanism replacing thetabu list: short-term memory, for the problem of minimizing production time of a set of tasks on machines while limiting the availability of machine operators.
Proceedings Article
Troop Search Optimization Algorithm for Unconstrained Problems.
Biplab Chaudhuri,Kedar Nath Das +1 more
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Multi-objective teaching-learning-based optimization of combined commercial fuel cells for electricity production
TL;DR: Based on multi-objective optimization, the paper finds that R123 is the optimal fluid for ORC based the thermo-economic performance in the cases of all fuel cells except the MCFC (300 kW).
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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