Equipment Selection for Mining: With Case Studies (Record no. 79372)
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000 -LEADER | |
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fixed length control field | 03528nam a22005775i 4500 |
001 - CONTROL NUMBER | |
control field | 978-3-319-76255-5 |
005 - DATE AND TIME OF LATEST TRANSACTION | |
control field | 20220801221155.0 |
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION | |
fixed length control field | 180302s2018 sz | s |||| 0|eng d |
020 ## - INTERNATIONAL STANDARD BOOK NUMBER | |
ISBN | 9783319762555 |
-- | 978-3-319-76255-5 |
082 04 - CLASSIFICATION NUMBER | |
Call Number | 629.04 |
245 10 - TITLE STATEMENT | |
Title | Equipment Selection for Mining: With Case Studies |
250 ## - EDITION STATEMENT | |
Edition statement | 1st ed. 2018. |
300 ## - PHYSICAL DESCRIPTION | |
Number of Pages | XIII, 155 p. 38 illus., 24 illus. in color. |
490 1# - SERIES STATEMENT | |
Series statement | Studies in Systems, Decision and Control, |
505 0# - FORMATTED CONTENTS NOTE | |
Remark 2 | Introduction -- Literature Review -- Match Factor Extensions -- Case Studies -- Single Location Equipment Selection -- Multiple Locations Equipment Selection -- Utilisation-based Equipment Selection -- Accurate Costing of Mining Equipment -- Future Research Directions. |
520 ## - SUMMARY, ETC. | |
Summary, etc | 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. |
700 1# - AUTHOR 2 | |
Author 2 | Burt, Christina N. |
700 1# - AUTHOR 2 | |
Author 2 | Caccetta, Louis. |
856 40 - ELECTRONIC LOCATION AND ACCESS | |
Uniform Resource Identifier | https://doi.org/10.1007/978-3-319-76255-5 |
942 ## - ADDED ENTRY ELEMENTS (KOHA) | |
Koha item type | eBooks |
264 #1 - | |
-- | Cham : |
-- | Springer International Publishing : |
-- | Imprint: Springer, |
-- | 2018. |
336 ## - | |
-- | text |
-- | txt |
-- | rdacontent |
337 ## - | |
-- | computer |
-- | c |
-- | rdamedia |
338 ## - | |
-- | online resource |
-- | cr |
-- | rdacarrier |
347 ## - | |
-- | text file |
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-- | rda |
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
-- | Transportation engineering. |
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
-- | Traffic engineering. |
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
-- | Computational intelligence. |
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
-- | Artificial intelligence. |
650 14 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
-- | Transportation Technology and Traffic Engineering. |
650 24 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
-- | Computational Intelligence. |
650 24 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
-- | Artificial Intelligence. |
830 #0 - SERIES ADDED ENTRY--UNIFORM TITLE | |
-- | 2198-4190 ; |
912 ## - | |
-- | ZDB-2-ENG |
912 ## - | |
-- | ZDB-2-SXE |
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