Controlling robotic mobile fulfillment systems and further topics in decision support / Marius Merschformann. Paderborn, 2019
Inhalt
- I Controlling Robotic Mobile Fulfillment Systems
- 1 Synopsis on RMFS
- 1.1 Distribution center process
- 1.2 Robotic Mobile Fulfillment System
- 1.3 Decision problems in RMFS control
- 1.4 Simulation
- 1.5 Research gap and scope
- 1.6 Paper summaries & contributions
- 1.7 Conclusion
- 2 RAWSim-O: A Simulation Framework for Robotic Mobile Fulfillment Systems
- 2.1 Introduction
- 2.2 The Robotic Mobile Fulfillment System
- 2.3 RAWSim-O
- 2.4 Demonstrator
- 2.5 Conclusion
- 2.6 Acknowledgements
- 3 Multi-Agent Path Finding with Kinematic Constraints for Robotic Mobile Fulfillment Systems
- 3.1 Introduction
- 3.2 Background
- 3.3 Search space
- 3.4 Algorithm design
- 3.5 Simulation study
- 3.6 Conclusion
- 3.7 Theorem
- 4 Decision rules for Robotic Mobile Fulfillment Systems
- 4.1 Introduction
- 4.2 The Robotic Mobile Fulfillment System
- 4.3 Related Work
- 4.4 Decision Problems
- 4.5 Decision Rules
- 4.6 Simulation Framework
- 4.7 Evaluation Framework
- 4.8 Computational Results
- 4.9 Conclusion
- 4.10 Upper bound on the unit throughput rate
- 5 Dynamic Policies for Resource Reallocation in a Robotic Mobile Fulfillment System with Time-Varying Demand
- 5.1 Introduction
- 5.2 Literature
- 5.3 Queueing Models
- 5.4 The Markov Decision Process
- 5.5 Stability Conditions
- 5.6 Validation & Numerical Experiments
- 5.7 Conclusions
- 5.8 AMVA Algorithm
- 5.9 Synchronization with a Load-dependent Queue
- 5.10 Stockout Probability
- 6 Active repositioning of storage units in Robotic Mobile Fulfillment Systems
- II Further topics on decision support
- 7 Synopsis on further topics
- 8 Structure-Preserving Instance Generation
- 8.1 Introduction
- 8.2 Related Work
- 8.3 Structure-preserving Instance Generation
- 8.4 Application to SAT and MaxSAT
- 8.5 Computational Evaluation
- 8.6 Conclusion and Future Work
- 9 Algorithm Configuration Applied to Heuristics for Three-Dimensional Knapsack Problems in Air Cargo
- 9.1 Introduction
- 9.2 Solution approach
- 9.3 Algorithm configuration approach
- 9.4 Computational results
- 9.5 Conclusion
- 10 Metaheuristics approach for solving personalized crew rostering problem in public bus transit