Please use this identifier to cite or link to this item: http://localhost/handle/Hannan/215
Title: Equipment Selection for Mining: With Case Studies
Authors: Burt, Christina N. ; author. ;;Caccetta, Louis. ; author. ;
subject: Engineering;Artificial Intelligence;Computational intelligence. ;;Transportation engineering. ;;Traffic engineering. ;;Engineering;Transportation Technology and Traffic Engineering. ;;Computational Intelligence. ;;Artificial Intelligence and Robotics
Year: 2018
place: Cham :
Publisher: Springer International Publishing :
Imprint: Springer,
Series/Report no.: Studies in Systems, Decision and Control, ; 2198-4182 ; ; 150 ;
Studies in Systems, Decision and Control, ; 2198-4182 ; ; 150 ;
Abstract: This unique book presents innovative and state-of-the-art computational models for determining the optimal truck–loader selection and allocation strategy for use in large and complex mining operations. The authors provide comprehensive information on the methodology that has been developed over the past 50 years, from the early ad hoc spreadsheet approaches to today’s highly sophisticated and accurate mathematical-based computational models. The authors’ approach is motivated and illustrated by real case studies provided by our industry collaborators. The book is intended for a broad audience, ranging from mathematicians with an interest in industrial applications to mining engineers who wish to utilize the most accurate, efficient, versatile and robust computational models in order to refine their equipment selection and allocation strategy. As materials handling costs represent a significant component of total costs for mining operations, applying the optimization methodology developed here can substantially improve their competitiveness. ;
Description: 



Printed edition: ; 9783319762548 ;
SpringerLink (Online service) ;

URI: http://localhost/handle/Hannan/215
More Information: XI, 155 p. 38 illus., 24 illus. in color. ; online resource. ;
Appears in Collections:مهندسی مدیریت ساخت

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Title: Equipment Selection for Mining: With Case Studies
Authors: Burt, Christina N. ; author. ;;Caccetta, Louis. ; author. ;
subject: Engineering;Artificial Intelligence;Computational intelligence. ;;Transportation engineering. ;;Traffic engineering. ;;Engineering;Transportation Technology and Traffic Engineering. ;;Computational Intelligence. ;;Artificial Intelligence and Robotics
Year: 2018
place: Cham :
Publisher: Springer International Publishing :
Imprint: Springer,
Series/Report no.: Studies in Systems, Decision and Control, ; 2198-4182 ; ; 150 ;
Studies in Systems, Decision and Control, ; 2198-4182 ; ; 150 ;
Abstract: This unique book presents innovative and state-of-the-art computational models for determining the optimal truck–loader selection and allocation strategy for use in large and complex mining operations. The authors provide comprehensive information on the methodology that has been developed over the past 50 years, from the early ad hoc spreadsheet approaches to today’s highly sophisticated and accurate mathematical-based computational models. The authors’ approach is motivated and illustrated by real case studies provided by our industry collaborators. The book is intended for a broad audience, ranging from mathematicians with an interest in industrial applications to mining engineers who wish to utilize the most accurate, efficient, versatile and robust computational models in order to refine their equipment selection and allocation strategy. As materials handling costs represent a significant component of total costs for mining operations, applying the optimization methodology developed here can substantially improve their competitiveness. ;
Description: 



Printed edition: ; 9783319762548 ;
SpringerLink (Online service) ;

URI: http://localhost/handle/Hannan/215
More Information: XI, 155 p. 38 illus., 24 illus. in color. ; online resource. ;
Appears in Collections:مهندسی مدیریت ساخت

Files in This Item:
File Description SizeFormat 
9783319762555.pdf3.04 MBAdobe PDFThumbnail
Preview File
Title: Equipment Selection for Mining: With Case Studies
Authors: Burt, Christina N. ; author. ;;Caccetta, Louis. ; author. ;
subject: Engineering;Artificial Intelligence;Computational intelligence. ;;Transportation engineering. ;;Traffic engineering. ;;Engineering;Transportation Technology and Traffic Engineering. ;;Computational Intelligence. ;;Artificial Intelligence and Robotics
Year: 2018
place: Cham :
Publisher: Springer International Publishing :
Imprint: Springer,
Series/Report no.: Studies in Systems, Decision and Control, ; 2198-4182 ; ; 150 ;
Studies in Systems, Decision and Control, ; 2198-4182 ; ; 150 ;
Abstract: This unique book presents innovative and state-of-the-art computational models for determining the optimal truck–loader selection and allocation strategy for use in large and complex mining operations. The authors provide comprehensive information on the methodology that has been developed over the past 50 years, from the early ad hoc spreadsheet approaches to today’s highly sophisticated and accurate mathematical-based computational models. The authors’ approach is motivated and illustrated by real case studies provided by our industry collaborators. The book is intended for a broad audience, ranging from mathematicians with an interest in industrial applications to mining engineers who wish to utilize the most accurate, efficient, versatile and robust computational models in order to refine their equipment selection and allocation strategy. As materials handling costs represent a significant component of total costs for mining operations, applying the optimization methodology developed here can substantially improve their competitiveness. ;
Description: 



Printed edition: ; 9783319762548 ;
SpringerLink (Online service) ;

URI: http://localhost/handle/Hannan/215
More Information: XI, 155 p. 38 illus., 24 illus. in color. ; online resource. ;
Appears in Collections:مهندسی مدیریت ساخت

Files in This Item:
File Description SizeFormat 
9783319762555.pdf3.04 MBAdobe PDFThumbnail
Preview File