Items related to Supporting Operational and Real-Time Planning Tasks...
Supporting Operational and Real-Time Planning Tasks of Road Freight Transport with Machine Learning: Guiding the Implementation of Machine Learning ... Information Systems and Management Science) - Softcover
Synopsis
World-wide trends such as globalization, demographic shifts, increased customer demands, and shorter product lifecycles present a significant challenge to the road freight transport industry: meeting the growing road freight transport demand economically while striving for sustainability. Artificial intelligence, particularly machine learning, is expected to empower transport planners to incorporate more information and react quicker to the fast-changing decision environment. Hence, using machine learning can lead to more efficient and effective transport planning. However, despite the promising prospects of machine learning in road freight transport planning, both academia and industry struggle to identify and implement suitable use cases to gain a competitive edge. In her dissertation, Sandra Lechtenberg explores how machine learning can enhance decision-making in operational and real-time road freight transport planning. She outlines an implementation guideline, which involves identifying decision tasks in planning processes, assessing their suitability for machine learning, and proposing steps to follow when implementing respective algorithms.
"synopsis" may belong to another edition of this title.
Buy New
View this item
£ 78.91
£ 14.97 shipping from U.S.A. to United Kingdom
Destination, rates & speedsSearch results for Supporting Operational and Real-Time Planning Tasks...
Seller Image
Supporting Operational and Real-Time Planning Tasks of Road Freight Transport With Machine Learning : Guiding the Implementation of Machine Learning Algorithms
Seller: GreatBookPrices, Columbia, MD, U.S.A.
Seller rating 5 out of 5 stars
Condition: New. Seller Inventory # 49216477-n
Quantity: 5 available
Stock Image
Supporting Operational and Real-Time Planning Tasks of Road Freight Transport with Machine Learning: Guiding the Implementation of Machine Learning . Information Systems and Management Science)
Published by
Logos Verlag Berlin GmbH, 2023
ISBN 10: 3832556303
ISBN 13: 9783832556303
New
Softcover
Seller: Kennys Bookshop and Art Galleries Ltd., Galway, GY, Ireland
Seller rating 5 out of 5 stars
Condition: New. Seller Inventory # V9783832556303
Quantity: 2 available
Seller Image
Supporting Operational and Real-Time Planning Tasks of Road Freight Transport With Machine Learning : Guiding the Implementation of Machine Learning Algorithms
Seller: GreatBookPrices, Columbia, MD, U.S.A.
Seller rating 5 out of 5 stars
Condition: As New. Unread book in perfect condition. Seller Inventory # 49216477
Quantity: 5 available
Stock Image
Supporting Operational and Real-time Planning Tasks of Road Freight Transport with Machine Learning
Seller: ISD LLC, Bristol, CT, U.S.A.
Seller rating 5 out of 5 stars
paperback. Condition: New. Seller Inventory # 1829191
Quantity: 5 available
Stock Image
Supporting Operational and Real-Time Planning Tasks of Road Freight Transport with Machine Learning: Guiding the Implementation of Machine Learning . Information Systems and Management Science)
Published by
Logos Verlag Berlin GmbH, 2023
ISBN 10: 3832556303
ISBN 13: 9783832556303
New
Softcover
Seller: Kennys Bookstore, Olney, MD, U.S.A.
Seller rating 5 out of 5 stars
Condition: New. Seller Inventory # V9783832556303
Quantity: 2 available
Stock Image
Supporting Operational and Real-Time Planning Tasks of Road Freight Transport with Machine Learning (Paperback)
Published by
Logos Verlag Berlin GmbH, Berlin, 2023
ISBN 10: 3832556303
ISBN 13: 9783832556303
New
Paperback
Seller: Grand Eagle Retail, Mason, OH, U.S.A.
Seller rating 5 out of 5 stars
Paperback. Condition: new. Paperback. World-wide trends such as globalization, demographic shifts, increased customer demands, and shorter product lifecycles present a significant challenge to the road freight transport industry: meeting the growing road freight transport demand economically while striving for sustainability.Artificial intelligence, particularly machine learning, is expected to empower transport planners to incorporate more information and react quicker to the fast-changing decision environment. Hence, using machine learning can lead to more efficient and effective transport planning. However, despite the promising prospects of machine learning in road freight transport planning, both academia and industry struggle to identify and implement suitable use cases to gain a competitive edge.In her dissertation, Sandra Lechtenberg explores how machine learning can enhance decision-making in operational and real-time road freight transport planning. She outlines an implementation guideline, which involves identifying decision tasks in planning processes, assessing their suitability for machine learning, and proposing steps to follow when implementing respective algorithms. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. Seller Inventory # 9783832556303
Quantity: 1 available
Stock Image
Supporting Operational and Real-Time Planning Tasks of Road Freight Transport with Machine Learning (Paperback)
Published by
Logos Verlag Berlin GmbH, Berlin, 2023
ISBN 10: 3832556303
ISBN 13: 9783832556303
New
Paperback
Seller: AussieBookSeller, Truganina, VIC, Australia
Seller rating 5 out of 5 stars
Paperback. Condition: new. Paperback. World-wide trends such as globalization, demographic shifts, increased customer demands, and shorter product lifecycles present a significant challenge to the road freight transport industry: meeting the growing road freight transport demand economically while striving for sustainability.Artificial intelligence, particularly machine learning, is expected to empower transport planners to incorporate more information and react quicker to the fast-changing decision environment. Hence, using machine learning can lead to more efficient and effective transport planning. However, despite the promising prospects of machine learning in road freight transport planning, both academia and industry struggle to identify and implement suitable use cases to gain a competitive edge.In her dissertation, Sandra Lechtenberg explores how machine learning can enhance decision-making in operational and real-time road freight transport planning. She outlines an implementation guideline, which involves identifying decision tasks in planning processes, assessing their suitability for machine learning, and proposing steps to follow when implementing respective algorithms. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability. Seller Inventory # 9783832556303
Quantity: 1 available