2016
DOI: 10.1111/itor.12296
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Review of metaheuristics applied to heat exchanger network design

Abstract: Heat exchanger networks (HENs) are a useful method of reducing the energy costs and environmental impact of industrial processes. Therefore, many papers focusing on solving HEN design problems efficiently have been published in the last years and several techniques have been proposed for their solution. The high complexity of the problem has led to an increment in the number of papers that use metaheuristics to solve it. The main reason is the capability of metaheuristics to handle complex problems in a feasib… Show more

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Cited by 40 publications
(13 citation statements)
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“…HENS is a NP-hard problem for which an exact polynomial-time computational algorithm does not exist [65]. Several metaheuristic techniques capable of handling complex problems in a feasible computational time have also been proposed [66,67].…”
Section: Heat Exchanger Network Synthesismentioning
confidence: 99%
“…HENS is a NP-hard problem for which an exact polynomial-time computational algorithm does not exist [65]. Several metaheuristic techniques capable of handling complex problems in a feasible computational time have also been proposed [66,67].…”
Section: Heat Exchanger Network Synthesismentioning
confidence: 99%
“…Nowadays, nature-inspired metaheuristic methods receive great attention [2], [15], [19], [21], [22]. In considered here problem some heuristic method including genetic algorithm [1], [13], memetic algorithm [20], scatter search [1] etc., are applied.…”
Section: Introductionmentioning
confidence: 99%
“…Another group of authors has applied optimization and heat transfer enhancement techniques to increase the equipment thermal performance (Reyes-Rodríguez & Moya-Rodríguez, 2016;Toimil & Gómez, 2017;Alam & Kim, 2018;Abdul-Wahhab et al, 2021). In this ambit, when heat exchangers network (HEN) retrofit methods are implemented, two main scenarios exist: fixed network structure, and topology modification.…”
Section: Introductionmentioning
confidence: 99%