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A MINLP study on shell and tube heat exchanger / O. Aras in Industrial & engineering chemistry research, Vol. 51 N° 43 (Octobre 2012) 

Public ISBD [article]  in Industrial & engineering chemistry research > Vol. 51 N° 43 (Octobre 2012) . - pp. 14158-14170 Titre : A MINLP study on shell and tube heat exchanger : Hybrid branch and bound/meta-heuristics approaches Type de document : texte imprimé Auteurs : O. Aras, Auteur ; M. Bayramoglu, Auteur Année de publication : 2013 Article en page(s) : pp. 14158-14170 Note générale : Industrial chemistry Langues : Anglais (eng) Mots-clés : Mathematical  programming  Heuristic  approach  Branch  and  bound  method  Heat  exchanger  Mixed  integer  programming  Non  linear  programming Résumé : Optimal design of shell and tube heat exchangers (STHE) has a crucial role in terms of the energy efficiency of plants. Therefore, it is currently one of the research topics of interest. In this study, a rigorous STHE design model strictly following TEMA standards and including various crucial constraints was established. Ten design variables of various kinds (continuous, integer, discrete, binary, and type) were selected for MINLP task. The handling of noncontinuous variables was attempted by means of three approaches including GA, PSO, and hybrid branch and bound methods over three case studies. Comparisons of the algorithms were performed using various performance criteria. Besides, the presence of noncontinuous variables in MINLP was analyzed. As a brief result, when type/binary/integer variables were included as optimization variables, very poor results were obtained, and hybrid PSO exhibited performance in each case superior to the others in terms of objective function value. ISSN : 0888-5885 En ligne : http://cat.inist.fr/?aModele=afficheN&cpsidt=26593343 [article] A MINLP study on shell and tube heat exchanger : Hybrid branch and bound/meta-heuristics approaches [texte imprimé] / O. Aras, Auteur ; M. Bayramoglu, Auteur . - 2013 . - pp. 14158-14170. Industrial chemistry Langues : Anglais (eng) in Industrial & engineering chemistry research > Vol. 51 N° 43 (Octobre 2012) . - pp. 14158-14170 Mots-clés : Mathematical  programming  Heuristic  approach  Branch  and  bound  method  Heat  exchanger  Mixed  integer  programming  Non  linear  programming Résumé : Optimal design of shell and tube heat exchangers (STHE) has a crucial role in terms of the energy efficiency of plants. Therefore, it is currently one of the research topics of interest. In this study, a rigorous STHE design model strictly following TEMA standards and including various crucial constraints was established. Ten design variables of various kinds (continuous, integer, discrete, binary, and type) were selected for MINLP task. The handling of noncontinuous variables was attempted by means of three approaches including GA, PSO, and hybrid branch and bound methods over three case studies. Comparisons of the algorithms were performed using various performance criteria. Besides, the presence of noncontinuous variables in MINLP was analyzed. As a brief result, when type/binary/integer variables were included as optimization variables, very poor results were obtained, and hybrid PSO exhibited performance in each case superior to the others in terms of objective function value. ISSN : 0888-5885 En ligne : http://cat.inist.fr/?aModele=afficheN&cpsidt=26593343

Optimization of scaled parameters and setting minimum rule base for a fuzzy controller in a lab - scale pH process / O. Aras in Industrial & engineering chemistry research, Vol. 50 N° 6 (Mars 2011) 

Public ISBD [article]  in Industrial & engineering chemistry research > Vol. 50 N° 6 (Mars 2011) . - pp. 3335-3344 Titre : Optimization of scaled parameters and setting minimum rule base for a fuzzy controller in a lab - scale pH process Type de document : texte imprimé Auteurs : O. Aras, Auteur ; M. Bayramoglu, Auteur ; A.S. Hasiloglu, Auteur Année de publication : 2011 Article en page(s) : pp. 3335-3344 Note générale : Chimie industrielle Langues : Anglais (eng) Mots-clés : pH  Optimization Résumé : Experimental and simulation studies were conducted to design a multiregional fuzzy logic controller (FLC) for a lab-scale pH process system. Scaled coefficients of the controller were optimized offline to obtain the best controller performance in terms of cost function and function evaluation number using two widely used global optimization methods; namely, Genetic Algorithm (GA) and Particle Swarm Optimization (PSO). Various tuning parameters of these optimization algorithms were investigated in detail to compare their performance on this subject. The cost functions obtained via two algorithms were very close to each other, but the function evaluation number was almost 4-fold due to complicated computation of the GA compared to the PSO. On the other side, working with the PSO was much easier owing to fewer adjustable parameters. In the second part of the study, the rule base of the controller was minimized using two different new methods. In this context, the number of rules was reduced by 43% and 56% using the fuzzy matching set and the personal initiative methods, respectively. Rule base reduction increased the performance and the effectiveness of the controller, an important issue for real-time applications. DEWEY : 660 ISSN : 0888-5885 En ligne : http://cat.inist.fr/?aModele=afficheN&cpsidt=23944501 [article] Optimization of scaled parameters and setting minimum rule base for a fuzzy controller in a lab - scale pH process [texte imprimé] / O. Aras, Auteur ; M. Bayramoglu, Auteur ; A.S. Hasiloglu, Auteur . - 2011 . - pp. 3335-3344. Chimie industrielle Langues : Anglais (eng) in Industrial & engineering chemistry research > Vol. 50 N° 6 (Mars 2011) . - pp. 3335-3344 Mots-clés : pH  Optimization Résumé : Experimental and simulation studies were conducted to design a multiregional fuzzy logic controller (FLC) for a lab-scale pH process system. Scaled coefficients of the controller were optimized offline to obtain the best controller performance in terms of cost function and function evaluation number using two widely used global optimization methods; namely, Genetic Algorithm (GA) and Particle Swarm Optimization (PSO). Various tuning parameters of these optimization algorithms were investigated in detail to compare their performance on this subject. The cost functions obtained via two algorithms were very close to each other, but the function evaluation number was almost 4-fold due to complicated computation of the GA compared to the PSO. On the other side, working with the PSO was much easier owing to fewer adjustable parameters. In the second part of the study, the rule base of the controller was minimized using two different new methods. In this context, the number of rules was reduced by 43% and 56% using the fuzzy matching set and the personal initiative methods, respectively. Rule base reduction increased the performance and the effectiveness of the controller, an important issue for real-time applications. DEWEY : 660 ISSN : 0888-5885 En ligne : http://cat.inist.fr/?aModele=afficheN&cpsidt=23944501