Journal ArticleDOI
Thermal-economic multi-objective optimization of plate fin heat exchanger using genetic algorithm
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In this article, the authors used the Fast and elitist non-dominated sorting genetic algorithm (NSGA-II) to obtain the maximum effectiveness and the minimum total annual cost (sum of investment and operation costs) as two objective functions.About:
This article is published in Applied Energy.The article was published on 2010-06-01. It has received 233 citations till now. The article focuses on the topics: Plate fin heat exchanger & NTU method.read more
Citations
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Journal ArticleDOI
Multi-objective optimization of heat exchangers using a modified teaching-learning-based optimization algorithm
R. Venkata Rao,Vivek Patel +1 more
TL;DR: 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.
Journal ArticleDOI
Development of a multicriteria tool for optimizing the renovation of buildings
Fanny Pernodet Chantrelle,Fanny Pernodet Chantrelle,Hicham Lahmidi,Werner Keilholz,Mohamed El Mankibi,Pierre Michel +5 more
TL;DR: In this article, a multi-criteria tool, MultiOpt, was developed for the optimization of renovation operations, with an emphasis on building envelopes, heating and cooling loads and control strategies.
Journal ArticleDOI
A systematic comparison of different S-CO2 Brayton cycle layouts based on multi-objective optimization for applications in solar power tower plants
TL;DR: A systematic comparison of different S-CO2 Brayton cycle layouts based on multi-objective optimizations suggests that the inter-cooling cycle layout and the partial-cooled cycle layout can generally yield the most excellent performances, and followed by the recompression cycle layouts and the pre-compression cycle layout, while the simple recuperation cycle layout has the worst performances.
Journal ArticleDOI
Plate heat exchangers: Recent advances
TL;DR: In this paper, the advances in plate heat exchangers both in theory and application are presented, and the direction of various technical research and developments in the field of energy handling and conservation is discussed.
Journal ArticleDOI
Techno-economic optimization of a shell and tube heat exchanger by genetic and particle swarm algorithms
TL;DR: In this paper, the use of genetic and particle swarm algorithms in the design of shell-and-tube heat exchangers is demonstrated, where a cost function (including costs of the heat exchanger based on surface area and power consumption to overcome pressure drops) is minimized.
References
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Book
Genetic algorithms in search, optimization, and machine learning
TL;DR: In this article, the authors present the computer techniques, mathematical tools, and research results that will enable both students and practitioners to apply genetic algorithms to problems in many fields, including computer programming and mathematics.
Journal ArticleDOI
A fast and elitist multiobjective genetic algorithm: NSGA-II
TL;DR: This paper suggests a non-dominated sorting-based MOEA, called NSGA-II (Non-dominated Sorting Genetic Algorithm II), which alleviates all of the above three difficulties, and modify the definition of dominance in order to solve constrained multi-objective problems efficiently.
Genetic algorithms in search, optimization and machine learning
TL;DR: This book brings together the computer techniques, mathematical tools, and research results that will enable both students and practitioners to apply genetic algorithms to problems in many fields.
Book
Neural Networks: A Comprehensive Foundation
TL;DR: Thorough, well-organized, and completely up to date, this book examines all the important aspects of this emerging technology, including the learning process, back-propagation learning, radial-basis function networks, self-organizing systems, modular networks, temporal processing and neurodynamics, and VLSI implementation of neural networks.
Book
Multi-Objective Optimization Using Evolutionary Algorithms
Kalyanmoy Deb,Deb Kalyanmoy +1 more
TL;DR: This text provides an excellent introduction to the use of evolutionary algorithms in multi-objective optimization, allowing use as a graduate course text or for self-study.
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