Passenger Rail Vehicle/Staff Deployment Optimization: Best ... · Passenger Rail Vehicle/Staff...
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Passenger Rail Vehicle/Staff Deployment
Optimization: Best Practices and Next Steps
June 22, 2016
Robert Mulder
President, IVU Traffic Technologies Inc
San Francisco, CA
IVU Traffic Technologies
Company History
1976IVU Founded
5 founders
Berlin
Roots in Operations
Research
2000Initial public offering
200 employees
Germany
Transportation planning
software tools
2016Customers ~500
440 employees
Worldwide
Software and hardware
Standard products
Optimization
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IVU Traffic Technologies AG
Represented Worldwide
Aachen Berlin Birmingham UKBogotáBudapest
FrankfurtHanoiHo Chi Minh CityMontrealParis
RomeSantiago de ChileSan Francisco Tel AvivVeenendaal
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The IVU.rail for the full range of
operational tasks
A common database for all modulesContinuous flow of information between the modulesProcess support via integrated optimization components (OPTI)
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What is Optimization?
Optimization means:
• Improving a current situation
• Getting to the optimum
Optimization in Rail:
• Setting rules for a problem solution
(e.g. duty length, maintenance rules)
• Defining an optimization goal (e.g.
saving vehicles, increase robustness)
• Obtaining a solution which
– obeys the rules
– is the optimum
– can be taken in production
“Optimization” is defined by you
Optimal
results
Permissibility (legal regulations,
fare rules)
Costs
(effective usage,
resource
conservation)
Social
acceptability
(duty lengths, break
times, happiness of
employees)
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Operational
Stability
(distribution,
uniformity)
For a range of scenarios, optimization tools will
result in savings for a typical rail road
Scenario Benefit
optimize annual crew schedule for on train
staff
Save 5%-15% of paid time
for complex scenarios
optimize annual equipment schedule incl.
consideration of maintenance capacities
reduction of downtimes leads to overall
savings on rolling stock
optimize assignment of duties and off days
sequences to employees
save overtime by balanced accounts +
increase fairness
simulation of “what if” scenarios:
new bids, negotiation of labor rules, depot
changes
solid decision support during negotiations
and for strategic issues
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Example: Optimization tools can generates optimized,
rule-compliant equipment schedules
layover capacities
maintenance rules and capacities
vehicle types and costs
compliant train formations
services(maintenance, cleaning, refuel)
non-revenue trips
uniformity
rule-compliant vehicle cycles
vehicle cycle rules(turnaround times, service times)
OPTIrequired passenger capacity
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Crew Schedule Optimization
• Goal: Crew scheduling
serving all equipment
schedules
• Complex rules:
– Duty type rules
– Duty type mix
– Restrict line changes
• Feature:
– Qualifications
– Stress routes
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Adjustment Optimization
• Goal: Small changes in the train schedule small changes in the crew schedule
– Train schedule changes due to constructions
– Extra trips for sport events or schools
– Friday timetable with small differences from Monday-Thursday timetable
• Rules:
– Keep crew schedule content similar, only add extra trips to existing duties
– Keep duty frames similar, only adjust start and end time within a limit
• Feature: Set a bonus for every duty that the optimization keeps equal or similar
Job Optimization
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• Goal: Job creation for a specific time period
• Rules:
• Fatigue and hours of service rules
• Soft and hard preference rules
• Feature:
– Profiles for different objectives, e.g. stability vs. lowest costs
– Check and verify intermediate solution in every moment
Currently being implemented at
VIA Rail in Montreal
Optimization Experience: Trenitalia
• Italy’s largest Railroad – regional commuter/freight/long-distance
• 8,000 trains per day with 14,000 employees
• Old System:
– Manual = each region planned vehicle and staff dispatch locally
– Redundant systems in place connected with proprietary interfaces
– Inefficient and unproductive
• New System:
– Standard software for all three rail types and specific rules for each
– Single database with use of standard interfaces
– Company work rules and legal requirements part of planning process
• Optimization brings great improvements:
– More reliable duties/jobs optimized by system
– “A new level of transparency and flexibility in duty planning scheduling and optimization” – Trenitalia Project Director
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Optimization Experience: Lessons Learned
Optimization is incorruptible:
Very often incorrect equipment schedules or crew schedules are discovered
Optimization detects unwritten rules
Optimization is complex:
Setup of parameters, especially in bigger scenarios, is a complex task
Profound knowledge of manual equipment and crew schedules is needed
Defining the optimization goal often needs a compromise between diverging
company interests
Optimization is a great scheduling automatic:
Calculated equipment and crew schedules are 100% correct according to rules
Scheduling process is more efficient (= faster, more often)
Quick calculation of different scenarios possible (e.g. for RFP’s, labor negotiations)
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Thank You!