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Design optimization of shell-and-tube heat exchangers using single objective and multiobjective particle swarm optimization

Designoptimierung von Rohrbündelwärmeaustauschern mit Hilfe monokriterieller und multikriterieller Partikel-Schwarm Optimierung
M. A. Elsays, M. Naguib Aly and A. A. Badawi
From the journal Kerntechnik


The Particle Swarm Optimization (PSO) algorithm is used to optimize the design of shell-and-tube heat exchangers and determine the optimal feasible solutions so as to eliminate trial-and-error during the design process. The design formulation takes into account the area and the total annual cost of heat exchangers as two objective functions together with operating as well as geometrical constraints. The Nonlinear Constrained Single Objective Particle Swarm Optimization (NCSOPSO) algorithm is used to minimize and find the optimal feasible solution for each of the nonlinear constrained objective functions alone, respectively. Then, a novel Nonlinear Constrained Multobjective Particle Swarm Optimization (NCMOPSO) algorithm is used to minimize and find the Pareto optimal solutions for both of the nonlinear constrained objective functions together. The experimental results show that the two algorithms are very efficient, fast and can find the accurate optimal feasible solutions of the shell and tube heat exchangers design optimization problem.


Der Partikel-Schwarm Optimierungsalgorithmus (PSO) wird angewendet zur Optimierung des Designs von Rohrbündelwärmeaustauschern und zur Bestimmung der optimalen Lösung, um so Versuch und Irrtum während des Entwurfsprozesses zu vermeiden. Die Erarbeitung des Entwurfs berücksichtigt den Arbeitsbereich und die jährlichen Gesamtkosten der Wärmetauscher als zwei Zielfunktionen zusammen mit betrieblichen und geometrischen Einschränkungen. Der nichtlineare, beschränkte, monokriterielle Partikel-Schwarm Optimierungsalgorithmus (NCSOPSO) wird verwendet, um die optimale Lösung für jede einzelne der nichtlinearen beschränkten Funktionen zu finden. Dann wird ein neuer nichtlinearer, beschränkter, multikriterieller Partikel-Schwarm Optimierungsalgorithmus (NCMOPSO) verwendet, um die Pareto-optimalen Lösungen für beide nichtlineare beschränkte Zielfunktionen zu finden. Die experimentellen Ergebnisse zeigen, dass beide Algorithmen sehr effizient und schnell sind und genaue optimale Lösungen des Rohrbündelwärmeaustauscher-Optimierungsproblems finden.


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Received: 2009-5-7
Published Online: 2013-04-05
Published in Print: 2010-03-01

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