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Alain Martinais, GIRO Inc., Montréal , Canada
Optimised allocation of vehicles to service taking into account light maintenance requests
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GIRO Inc.
• Experts in productivity solutions since 1979
• Recognised world leading solutions • Public transport • Adapted transport • Postal services
• The last four UITP host cities, Helsinki, Vienna, Dubai, and Geneva rely on GIRO’s HASTUS™ solution
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• Integrated software suite – Scheduling and operations – Customer information – Planning and analysis – All modes and types
• Recognised industry leader
• Over 30 years of innovation
• Extensive collaboration with leading agencies and universities
HASTUS
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The history of PlanBus
• Round tables in user groups addressed subject
• Targeted meetings with interested parties
• Early implementation of a semi-automatic solution (list processing) • Use of user-defined fields and attributes (client specific)
• Preliminary algorithm design based on our PlanOpt solution, enhanced to address the task complexity
• Project with client to implement new generic PlanBus • Adjustment of HASTUS data model • Algorithm development and tests with real problems
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Resolving vehicle assignment
• A complex task: • Large number of vehicles • Wide variety of vehicle models and characteristics • Multiple requirements: capacity, equipment, livery,
advertisement, etc. • Parking constraints • Maintenance synchronisation • Even use of vehicles within a lot
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Resolving vehicle assignment
• Often best assignment = best compromise • At least respect most important criteria • Still difficult to attain without tools
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Adjustments to HASTUS data model
• Adjustment to existing objects: • More details for individual vehicle characteristics
• New objects:
• Vehicle coverage requirements
• Maintenance activities
• Maintenance activity requests
• Maintenance capacity at depots
• Vehicle assignment rules
• Vehicle assignment procedures
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Optimisation
• Minimum cost of a network flux problem with multiple iterations
• Possibility to define multiple procedures • Different depots/divisions/subset of network • Different planning horizons • Different rules and parameters • Control of maintenance activities generation
• Possibility to fix portions of the solution
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Vehicles
C ij
0
C ij
1
C ij
2
C0
11
C1
11
C2
11
Veh1
Veh n
Veh 2
Veh i
Block 1
Block 2
Block m
Block j
C0
12
C1
12
C2
13
f (free) Free
C if
0
C if
1
0
6102
Flux 1 Flux 1
1 1
1
1
1
1
adjusted adjusted
Optimisation
C if
2
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Initial implementation (2012)
Blocks
Vehicle coverage
requirements
Maintenance activity requests
PlanBus
Blocks
Maintenance capacity
Assignment rules
Assignment solution: vehicle task-vehicle ID
& maintenance activities
Available vehicles
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Evolution
• Initial version provided all functions required by our client
• Mini algorithm “BestNext” implemented in 2013
• On the drawing board: • Consider depot layout, circulation constraints, and
parking location on return • Take into account rail constraints • And more….
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Conclusions
• System has now been running every day for over six months
• Initial performance and stability issues quickly resolved
• Results with PlanBus much better than previous manual processes
• Significant gains were observed meeting vehicle allocation targets
• PlanBus introduction allowed reduction in peak vehicle requirements