Optimization Techniques and their Applications to Mine Systems
Language: English
Published by CRC Press, 2025
- Softcover
- New

Seller: AHA-BUCH GmbH, Einbeck, GermanyAHA-BUCH GmbH
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Add to basketItem description from seller
nach der Bestellung gedruckt Neuware - Printed after ordering - This book describes the fundamental and theoretical concepts of optimization algorithms, along with their potential applications and implementation strategies in mining engineering. Reliability analysis of mine systems, inventory management in mines, and applications of non-linear optimization are discussed with examples and numerical problems.
Seller Inventory # 9781032060996
- Title
- Optimization Techniques and their Applications to Mine Systems
- Author
- Snehamoy Chatterjee
- Publisher
- CRC Press
- Publication year
- 2025
- Condition
- Neu
- Binding
- Taschenbuch
- Language
- English
- ISBN 10
- 1032060999
- ISBN 13
- 9781032060996
- Item weight
- 761 grams
- Dimensions
- 254x178x22 mm
This book describes the fundamental and theoretical concepts of optimization algorithms in a systematic manner, along with their potential applications and implementation strategies in mining engineering. It explains basics of systems engineering, linear programming, and integer linear programming, transportation and assignment algorithms, network analysis, dynamic programming, queuing theory and their applications to mine systems. Reliability analysis of mine systems, inventory management in mines, and applications of non-linear optimization in mines are discussed as well. All the optimization algorithms are explained with suitable examples and numerical problems in each of the chapters.
Features include:
• Integrates operations research, reliability, and novel computerized technologies in single volume, with a modern vision of continuous improvement of mining systems.
• Systematically reviews optimization methods and algorithms applied to mining systems including reliability analysis.
• Gives out software-based solutions such as MATLAB®, AMPL, LINDO for the optimization problems.
• All discussed algorithms are supported by examples in each chapter.
• Includes case studies for performance improvement of the mine systems.
This book is aimed primarily at professionals, graduate students, and researchers in mining engineering.
"Synopsis" may belong to another edition of this title.
About the Author
Amit Kumar Gorai is an Associate Professor in the Department of Mining Engineering at National Institute of Technology, Rourkela, India. Prior to join at NIT Rourkela, Dr. Gorai has worked at Birla Institute of Technology Mesra, Ranchi for over 7 years. He has published over 60 research articles on reliability, machine learning, remote sensing, environment, etc. In addition, Dr. Gorai has written 1 guide book, ‘A Complete Guide for Mining Engineers’ and 1 edited book, ‘Sustainable Mining Practices’. Dr. Gorai has received his Ph.D. from Indian School of Mines, Dhanbad. He has worked as an Endeavour Executive Fellow at the University of New South Wales, Sydney, Australia, and Raman Postdoctoral Fellow at Jackson State University, MS, USA. He has been teaching Mine Systems Engineering at NIT Rourkela for last 5 years. He has completed several sponsored research projects in the field of environmental modelling for different government organizations. His current research area is systems optimization, machine learning, GIS and Remote Sensing. Gorai is a life member of the Institution of Engineers India (IEI), The Mining, Geological & Metallurgical Institute (MGMI) of India.
Snehamoy Chatterjee is an Assistant Professor of Mining Engineering in the Department of Geological and Mining Engineering and Sciences at Michigan Technological University. Before joining Michigan Tech, Chatterjee was working as an Assistant Professor at the National Institute of Technology, Rourkela, India. Chatterjee specializes in ore reserve estimation, short- and long-range mine planning, mining machine reliability analysis, mine safety evaluation, and the application of image analysis and artificial intelligence in mining problems. He received his Ph.D. in Mining Engineering from the Indian Institute of Technology Kharagpur, India. Chatterjee worked as a Post-Doctoral Fellow at the University of Alaska Fairbanks, and as a research associate at COSMO Stochastic Mine Planning Laboratory, McGill University, Canada, where he focused on mine planning optimization and ore-body modeling under uncertainty. Presently, Chatterjee is actively involved in research work in the field of resource modeling, production planning, and online quality monitoring, integrating multiple data types. He is teaching courses and advising students on topics related to mine planning, mineral resource modeling, mining machine reliability, and vision-based online quality monitoring. He has completed several sponsored research and industry projects in these fields for different government organizations and mining companies in India and the USA.
Chatterjee is an active member of the International Associate of Mathematical Geosciences (IAMG), the Society for Mining, Metallurgy, and Exploration, Inc. (SME), the Society of Mining Professors (SOMP). He has served as a co-convener and a technical committee member for several international mining conferences. He is also a reviewer for more than twenty journals and has received The Editor's Best Reviewer Awards 2014 from Mathematical Geosciences Journal. He is the recipient of the 2015 APCOM Young Professional Award at the 37th APCOM in Fairbanks, Alaska. He is an editorial board member of International Journal of Mining, Reclamation, and Environment and Artificial Intelligence Research journal, and associate editor of Results in Geophysical Sciences.
"About the title" may belong to another edition of this title.
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