A genetic algorithm for operation optimization of an industrial cogeneration system

Manolas, DA; Gialamas, TP; Frangopoulos, CA; Tsahalis, DT

dc.contributor.author	Manolas, DA	en
dc.contributor.author	Gialamas, TP	en
dc.contributor.author	Frangopoulos, CA	en
dc.contributor.author	Tsahalis, DT	en
dc.date.accessioned	2014-03-01T01:11:35Z
dc.date.available	2014-03-01T01:11:35Z
dc.date.issued	1996	en
dc.identifier.issn	0098-1354	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/11728
dc.subject	Continuous Variable	en
dc.subject	Genetic Algorithm	en
dc.subject	Genetics	en
dc.subject	Objective Function	en
dc.subject	Optimization Problem	en
dc.subject	Simulation Model	en
dc.subject	Expert System	en
dc.subject.classification	Computer Science, Interdisciplinary Applications	en
dc.subject.classification	Engineering, Chemical	en
dc.title	A genetic algorithm for operation optimization of an industrial cogeneration system	en
heal.type	journalArticle	en
heal.identifier.primary	10.1016/0098-1354(96)00192-5	en
heal.identifier.secondary	http://dx.doi.org/10.1016/0098-1354(96)00192-5	en
heal.language	English	en
heal.publicationDate	1996	en
heal.abstract	Genetic Algorithms (GAs) have been developed in the last three decades in an attempt to imitate the mechanics of the selection process in natural genetics. They also contain many elements of expert systems. In the present work, a GA is applied for the optimization of the operation of a cogeneration system, which supplies a process plant with electricity and steam at various pressure levels. A mathematical simulation model of the system has been developed taking into consideration the real conditions of the main equipment, as determined by an appropriate set of measurements. The GA is combined with the simulation model in order to solve the optimization problem under specified constraints. The capability of GAs to handle objective functions of any complexity with both discrete (e.g., integer) and continuous variables, as well as their capability of optimizing only on the basis of the results of the simulation model, make GAs successful in this type of problems.	en
heal.publisher	PERGAMON-ELSEVIER SCIENCE LTD	en
heal.journalName	Computers and Chemical Engineering	en
dc.identifier.doi	10.1016/0098-1354(96)00192-5	en
dc.identifier.isi	ISI:A1996UR31000057	en
dc.identifier.volume	20	en
dc.identifier.issue	SUPPL.2	en
dc.identifier.spage	S1107	en
dc.identifier.epage	S1112	en