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Roster OptimizerCreation of a work roster to cover an irregular demand, with minimal lost hours.

Version 2 – March 21st 2013lo

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Case Description: Inputs

Planning of staff for check-in security at Brussels Airport.

2 piers: pier A and pier B

Very irregular demand curve

500 people

Variety of working regimes

Specific planning requirements

- Plan 50% male and 50% female agents

- Competences: 1 out of 4 must be “screener”

- Shift types: The types of eligible shifts (start, end, duration) are defined

- Various agent/shift preferences

- Car-Pooling groups: people coming to work together need to be planned

together

- …

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Generic Case

Optimal match between required capacity and available capacity, given

- Irregular pattern of required capacity

- Demand for specific requested competences

- Personnel with specific working regulations

- Personnel with specific competences

- Multiple geographical sites

Where does it occur ?

- Airport security

- Airport catering

- Airport ground operations

- Sorting of postal flows

- Road assistance services

- Police services

- Organisation of events …

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Case Description: The Problem

Find the collection of shifts (part-time, full-time) that avoids

unproductive hours:

Satisfying all planning rules (competences, balances, working regimes,

preferences, …)

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Demo: Data to Plan

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Demo: Start a Demo Run

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Problem resolution process

The optimizer generates ready to use shift plan

Phase 1 • Make a rough shift planning

Phase 2• Make a detailed shift planning

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Problem resolution process

The optimizer generates ready to use shift plan

Phase 1 • Make a rough shift planning

Phase 2• Make a detailed shift planning

Phase 3• Plan, breaks, short rests, additional tasks, …

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Demo: Show solution, plan breaks

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Variations on the rostering problem

Handle standard generic working regimes or working regimes tuned to

the individual

Define a generic work roster to be rolled-out, or define a new work

roster for every new planning period

Define an unallocated work roster or allocate shifts to the individual

Build a roster from scratch or build a roster around existing shifts

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Simulations and Release

Generate Multiple Scenario’s, play with

- Use only own staff, or also freelance staff

- Require strict abeyance of the rules or loosen with penalties

- Change the balance between cost optimality and service level

- ….

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Simulations and Release

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Simulations and Release

Generate Multiple Scenario’s, play with

- Use only own staff, or also freelance staff

- Require strict abeyance of the rules or loosen with penalties

- Change the balance between cost optimality and service level

- ….

Compare different simulations and choose the best one

Release the preferred result

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Demo: Release Planning and Generate Conflict

Conflict generated

by hand.

Optimizer does not

return conflicts

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Demo: Restart optimizer with respect planning

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Results

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Test simulations overview

demand planned coverage # agents #shifts time

(hours) (hours) (wrt demand) (wrt ref plan) (wrt ref plan)

Reference plan 100% 131.56% 131.59% 100% 100% 5 days

5 people

Optimal Simulation 100% 107.49% 107.51% 94.59% 129.16% 10h44

1 person

Simulation targeting 100% 118.78% 118.81% 94.59% 134.27% 8h44

20% over-capacity 1 person

Simulation targeting 100% 118.11% 118.31% 93.86% 112.35% 9h57

20% over-capacity 1 person

+ car-pooling and

un-employment

Simulation done on real data-set from May 2012

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Other Simulations

The simulations in Brussels consider highly constrained cases (very

specific working regimes, shift types and preferences)

Other simulations (airport of Lyon) have given even stronger

optimizations (reduction of 8000 idle hours to 300 idle hours in a

planning horizon of one month).

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Conclusions

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Conclusions

Rosters tend to be periodic, rather stable, often hand-crafted

When the need for services is less stable, the match is between

available and required service time is not perfect

This results in a high extra cost

The work roster optimization can find a far better match.

This can imply a very high cost saving

It can take into account very specific business rules or employee

preferences

To maximize the savings, a higher flexibility of your employees is

required as well