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!