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Algorithm Engineering of Timetable Information
Published on Oct 02, 20123486 Views
How to find attractive connections in public transportation for a planned trip is a challenging multi-criteria search problem which appears in several variants: as a pre-trip planning problem as wel
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Chapter list
Algorithm Engineering of Timetable Information00:00
How To Travel?00:10
Public Transport = Schedule-Based Travelling (1)01:19
Public Transport = Schedule-Based Travelling (2)02:08
From Printed Schedule Books to Fully Electronic Timetable Information02:29
Timetable Information Systems: The Classical Use (1)03:00
Timetable Information Systems: The Classical Use (2)03:30
Usage of Timetable Information Systems04:16
Algorithmic Engineering enters ... (1)05:04
Algorithmic Engineering enters ... (2)05:43
Event-Activity Networks Time-Expanded Network Model06:20
Earliest Arrival Problem (1)08:38
Earliest Arrival Problem (2)09:42
Success Story of Algorithm Engineering: Classical s-t Shortest Paths10:27
Example11:48
Example: Real Query (1)12:42
Example: Real Query (2)12:58
Example: Real Query (3)13:43
What is Wrong?14:30
Overview15:14
Towards More Realistic Models (1)16:18
Towards More Realistic Models (2)17:02
Alternative Graph Models (1)18:04
Alternative Graph Models (2)18:52
Time-Dependent Graph Model19:43
Brief Discussion of Models20:10
Overview (2)20:58
Multi-Criteria Search (1)21:05
Multi-Criteria Search (2)22:08
Fare Zones in London24:41
Pareto-Optimality25:28
Size of Pareto Set26:08
Attractive Alternatives27:16
Multi-Criteria Dijkstra Algorithm (1)28:30
Multi-Criteria Dijkstra Algorithm (2)29:39
A Dilemma30:22
Techniques that do not work as well as expected ...31:39
Transfer Patterns (Bast et al., ESA 2010) (1)32:24
Transfer Patterns (Bast et al., ESA 2010) (2)34:01
Transfer Patterns (Bast et al., ESA 2010) (3)34:31
Round-Based Search (1)34:52
Round-Based Search (2)36:22
Overview (3)36:56
Delays and Cancellations37:01
Realtime Train Information (1)37:21
Realtime Train Information (2)37:57
Secondary Delays38:04
Static Delay Propagation38:54
Massive Delay Streams40:24
Typical Delay Message (simpli ed)40:47
Delay Propagation41:14
MOTIS (developed with Mathias Schnee) (1)41:53
MOTIS (developed with Mathias Schnee) (2)42:07
MOTIS - Example (1)42:20
MOTIS - Example (2)42:24
Applications of Realtime Train Information42:27
MOTIS - Example (3)43:03
Transfer into Practice (1)43:18
Transfer into Practice (2)43:59
Transfer into Practice (4)44:13
Example: Real Query (4)45:17
Overview (4)46:08
Robust Timetable Information46:54
Uncertainty Sets47:43
Results47:53
Strict Robustness49:17
Price of "Light Robustness"49:47
Stochastic Delay Propagation51:03
Model Assumptions (1)52:40
Model Assumptions (2)53:20
Model Assumptions (3)53:36
Model Assumptions (4)53:49
Model Assumptions (5)54:10
Experiment: Predictions over time55:08
Overview (5)55:21
Final Thoughts55:26
Future Work - Challenges (1)56:26
Future Work - Challenges (2)56:53
Future Work - Challenges (3)57:19