Presenting the results of a research project investigating autonomous adaptation of vehicle schedules, this monograph develops and evaluates a number of forward-thinking ideas for the management of transportation processes in volatile scenarios.

This monograph presents results originating from a research project investigating autonomous adaptation of vehicle schedules and systematically develops and evaluates innovative ideas for the management of transportation processes in volatile scenarios. Showing the progress made in the development of the methodological toolbox for decision support in dynamic process management is the major motivation behind this book. The result is a new integrated approach to dynamic decision making.

Existing process planning approaches for volatile environments and their application boundaries are investigated in Part I. Part II introduces the concept of feedback-controlled adaptive decision models and proposes the required extensions of the online decision making framework and of multi-agent systems. A comprehensive evaluation of the proposed decision model adaptation framework based on computational simulation experiments is reported in Part III and demonstrates the predominance of the new approach.

Distinguishing features of this book are:

-It provides the first contribution to the operational management of processes in supply networks that explicitly addresses the two challenges of dynamics and distributed decision making simultaneously.

-It systematically approaches the limits of model-based process planning but also proposes methods to extend the application boundaries.

-Software prototypes are developed and a comprehensive evaluation within numerical simulation experiments is executed.

-The observed results are discussed with an explicit focus on specific performance indicators (flexibility, stability and robustness).

-The strict interdisciplinary approach merging the requirements and needs of management sciences, operations research and computer sciences is pursued throughout the book.

Presents a novel new approach to dynamic decision making in logistics/supply chain Illustrates how adaptive decision models can better manage supply chains Proposes new approaches to software development for supply chain management Includes supplementary material: sn.pub/extras

Autorentext

Dr. Dmitry Ivanov is a Professor of Supply Chain and Operations Management and Director of the Digital-AI Supply Chain Lab at the Berlin School of Economics and Law (HWR Berlin), Germany. For 25 years, he has taught operations management, supply chain management, and logistics at the undergraduate, graduate, PhD, and executive MBA levels. He is an internationally renowned expert in supply chain and operations management, industrial and control engineering, and artificial intelligence. He has authored over 470 publications, including over 180 papers in international academic journals and several books published with Springer. He has made fundamental and influential contributions, particularly exploring structural dynamics and control in complex networks with applications to supply chain resilience, Industry 4.0, supply chain simulation, risk analytics, and digital supply chain twins. Author of the Viable Supply Chain Model and founder of the ripple effect research. He is an active editor for several leading international journals and chairs major international conferences. Dr. Alexander Tsipoulanidis, MBA, is a Professor of Supply Chain and Operations Management at the Berlin School of Economics and Law (HWR Berlin), Germany. He has over 25 years of international experience in factory planning and restructuring, optimizing existing operations, and supply chain and operations consulting. Dr. Tsipoulanidis has led teams to conduct "Lean Operations Assessments" within a production network spanning more than 40 international sites, has implemented SCM collaboration portals, and has run global SCM efficiency and restructuring programs. His research focuses on supply chain excellence and lean operations during the digital transformation. Dr. Jörn Schönberger is a Professor of Business Management at the Technical University of Dresden, Germany, where he holds the Chair of Transport Services and Logistics as part of the Friedrich List Faculty of Transportation and Traffic Science. Before his current position, he was a Professor of Supply Chain and Operations Management at the Berlin School of Economics and Law (BSEL), Germany, and a senior researcher at the University of Bremen, Germany. He has been involved in several academic programs at different study levels in Germany and abroad, offering various courses at the interface of engineering and business management. His research interests include the model-based optimization and control of complex logistics systems, and the synchronization of information and material flows.

Inhalt
Process Planning in Supply Consortia.- Transport Processes and Uncertainty.- Decision Support: Applying the State-of-the-Art.- Decision Support in Principal-Agent-Relationships.- Adaptive Controllers for Mathematical Optimization Models.- Responsiveness Improvement.- Nervousness Reduction in Re-Scheduling.- Impacts on Robustness.- Summary and Conclusions.