Optimization of power and heating systems based on a new hybrid algorithm

A novel combination of Particle Swarm Optimization (PSO) and Genetic Algorithm (GA) is applied on a base case cogeneration optimization problem called the modified CGAM problem with two objective functions. The first objective function, the exergetic efficiency, should be maximized and the second on...

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Main Authors:	M.J. Mahmoodabadi, A.R. Ghavimi, S.M.S. Mahmoudi
Format:	Article
Language:	English
Published:	Elsevier 2015-09-01
Series:	Alexandria Engineering Journal
Subjects:	CGAM problem Exergoeconomic optimization Hybrid algorithms Particle swarm optimization Genetic algorithm
Online Access:	http://www.sciencedirect.com/science/article/pii/S1110016815000691

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spelling	doaj-75941de0a768448aa28ed7122b3624f32021-06-02T01:32:43ZengElsevierAlexandria Engineering Journal1110-01682015-09-0154334335010.1016/j.aej.2015.04.011Optimization of power and heating systems based on a new hybrid algorithmM.J. Mahmoodabadi0A.R. Ghavimi1S.M.S. Mahmoudi2Department of Mechanical Engineering, Sirjan University of Technology, Sirjan, IranFaculty of Mechanical Engineering, University of Tabriz, Tabriz, IranFaculty of Mechanical Engineering, University of Tabriz, Tabriz, IranA novel combination of Particle Swarm Optimization (PSO) and Genetic Algorithm (GA) is applied on a base case cogeneration optimization problem called the modified CGAM problem with two objective functions. The first objective function, the exergetic efficiency, should be maximized and the second one is the total cost rate that should be minimized. The effects of important parameters, such as equivalence ratio, emission, and unit cost of fuel are studied on the exergetic and economic performance of the system.http://www.sciencedirect.com/science/article/pii/S1110016815000691CGAM problemExergoeconomic optimizationHybrid algorithmsParticle swarm optimizationGenetic algorithm
collection	DOAJ
language	English
format	Article
sources	DOAJ
author	M.J. Mahmoodabadi A.R. Ghavimi S.M.S. Mahmoudi
spellingShingle	M.J. Mahmoodabadi A.R. Ghavimi S.M.S. Mahmoudi Optimization of power and heating systems based on a new hybrid algorithm Alexandria Engineering Journal CGAM problem Exergoeconomic optimization Hybrid algorithms Particle swarm optimization Genetic algorithm
author_facet	M.J. Mahmoodabadi A.R. Ghavimi S.M.S. Mahmoudi
author_sort	M.J. Mahmoodabadi
title	Optimization of power and heating systems based on a new hybrid algorithm
title_short	Optimization of power and heating systems based on a new hybrid algorithm
title_full	Optimization of power and heating systems based on a new hybrid algorithm
title_fullStr	Optimization of power and heating systems based on a new hybrid algorithm
title_full_unstemmed	Optimization of power and heating systems based on a new hybrid algorithm
title_sort	optimization of power and heating systems based on a new hybrid algorithm
publisher	Elsevier
series	Alexandria Engineering Journal
issn	1110-0168
publishDate	2015-09-01
description	A novel combination of Particle Swarm Optimization (PSO) and Genetic Algorithm (GA) is applied on a base case cogeneration optimization problem called the modified CGAM problem with two objective functions. The first objective function, the exergetic efficiency, should be maximized and the second one is the total cost rate that should be minimized. The effects of important parameters, such as equivalence ratio, emission, and unit cost of fuel are studied on the exergetic and economic performance of the system.
topic	CGAM problem Exergoeconomic optimization Hybrid algorithms Particle swarm optimization Genetic algorithm
url	http://www.sciencedirect.com/science/article/pii/S1110016815000691
work_keys_str_mv	AT mjmahmoodabadi optimizationofpowerandheatingsystemsbasedonanewhybridalgorithm AT arghavimi optimizationofpowerandheatingsystemsbasedonanewhybridalgorithm AT smsmahmoudi optimizationofpowerandheatingsystemsbasedonanewhybridalgorithm
_version_	1721409630329896960

Optimization of power and heating systems based on a new hybrid algorithm

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