• Vehicle breakdown• Change in transportation requests• Arrival of new transportation requests• Disruption on infrastructure

• impact of incident• duration of incident

• Set of autonomous vehicles• Transportation infrastructure of resources• Set of transportation requests:

for each request, find a conflict-free shortest path• head-on conflicts• catching-up conflicts

• Taking into account malfunctioning vehicles and resources

Problem description

Incidents

before / after CPU Speed Performance Robustness

TR + - -

FPS + 0 -

TWGR - / 0 + - / 0• Traffic rules and zone control (TR)

• Only allow actions that can never lead to a conflict

• Fixed path scheduling (FPS)• Insert waiting times for best schedule

along pre-determined path• Job Shop Scheduling with blocking

• Time window graph routing (TWGR)• Search through graph of free time windows• Avoiding planned movements of others

• Introduce slack into routing schedules• Multi-objective routing:

• efficiency• reliability

• Robustness of planning and execution method combined

• Impact of bi-directional resources

Dest.

• Factory shop floor• Transportation order from one

machine to another• bi-directional lanes• dynamic environment

• AGV container terminal• Highly structured infrastructure• Transportation orders in large batches

• Airport taxiing• Congestion in peak hours and exceptional

weather conditions• Multi-stage routing problem• Mostly uni-directional taxiways

• Smart conflict prevention: from explicit constraintchecking to off-line encoding of constraints into freetime windows

• Complexity: from O(n2v4) to O(nv · log(nv) + n2v)• Better spread of agents over space and time results

in better performance• A*-search through graph of free time windows

Fixed Path Scheduling is very fast, but Time Window Graph Routing also finds a solution within 0.5s.

Repeated use of Fixed Path algorithms leads to overuse of key resources.Time Window Graph routing provides spread of agents over space and time.

TWGR is an optimal planning algorithm for a single-agent.

Order in which agents plan is important for individual plan quality.

For the Schiphol airport experiments, the order in which agents plan is not of great importance to system performance.

The red truck has reserved its plan. Now, the blue truck wants to plan a routeto its destination e4.

Context-Aware Logistic Routing and SchedulingAdriaan ter Mors, AlmendeJonne Zutt, Cees Witteveen, Algorithmics, Faculty of EEMCS, TU Delft

Adriaan ter Mors Jonne ZuttCees Witteveen

adriaan@almende.orgj.zutt@tudelft.nlc.witteveen@tudelft.nl

Gridlock

From a2 two free time windows in b2 can be reached. Only the later window can reach a free time window in c2.

a b c d e

1

2

3

4

5

The shortest-time path is to go via a5.

TWGR with heuristicTWGR no heuristicTWGR no cyclesFPS

TWGR with heuristicTWGR no heuristicTWGR no cyclesFPS

TWGR with heuristicTWGR no heuristicTWGR no cyclesFPS

TWGR with heuristicTWGR no heuristicTWGR no cyclesFPS

Example time window graph

TWGR versus FPS

Total vs. single plan quality

Example time window graph

Coping with incidents

Time window graph routing

Methods