dynamic scheduling in mobile workforce management

© British Telecommunications plc 2001

Dynamic Scheduling in Mobile Workforce Management

Ralf Keuthen


Contents

Automated Mobile Workforce Management The Workforce Scheduling Problem TASKFORCE System Overview Issues Current/Future Work


Mobile Workforce Management a.p.solve -- A Short History

Involved in mobile workforce management since 1987.

Produced two major Work Management Systems which have evolved into the TASKFORCE products we currently market.

a.p.solve (100+ employees) was spun out via the British Telecom’s Brightstar business incubator initiative in April 2003.

a.p.solve’s planning and scheduling products primarily support the management of mobile workers via Personal Digital Assistants and mobile telephony.


Scope

Large telecommunication, cable, utility and fix & repair companies typically maintain a fieldforce of 100s - 10,000s of technicians

The fieldforce supplies provision of service, repair and maintenance tasks on a daily basis (between 1000s - 100,000s of tasks/day)

Customers Residential, Business (provision, repair) Company itself (maintenance, repair)


Example: Mobile Workforce at British Telecom

BT Customer Access: a.p.solve’s TASKFORCE products currently

schedule BT’s workforce of Service Technicians.

~25,000 field technicians ~150,000 tasks every day across the United

Kingdom. A high quality service at low operational cost

needs to be delivered.


Work Management Organisation

Domains: Geographical

partition of the work area

into autonomous domains

Domains controlled by automated work management system

Supervised by a human controller


Organisation: How it works

• Call Centre

• Network Service

TASKFORCE

• Handheld terminal

• Laptop

• Mobile

Customer Service

Work allocation and visualisation

Dispatch work to technicians


Organisation: How it works Customer Service:

take customer calls arrange appointments

TASKFORCE: provide customer service with a selection of

appointment slots Allocate work to technicians dispatch work to technicians

Technicians receive work details travel to and carry out work report back when work is finished


Workforce Management: From a Scheduling Point of View


Scheduling Model

Resources: Technicians Vehicles and other equipment

Activities: provision, repair and maintenance work

Constraints: time windows, access restrictions precedence constraints co-op, assists, etc.


Main ObjectivesRight man - right time - right place - right costs

Maximise productivity number of tasks scheduled most efficient resource for each task

Ensure a high quality of service compliance with agreed appointments & due dates work importance

- Minimise costs travel times waiting/idle times overtime


Other Objectives Workforce satisfaction

task preferences preferred working areas

Business rules every technician gets a job avoid task splitting (when possible)

Avoid disturbances robust schedules flexible schedule

Some of these contradict one another


Issues

Dynamics/Uncertainties/Complexities of problem

Scale

The need for a totally automated, online, system.


Dynamics

Tasks

The company and its customers can request cancel amend tasks (at all time!!)

ResourcesAvailability subject to last minute changes personal absence, sick leave, etc changes to task completion times vehicle breakdown


Uncertainties Duration of tasks

Uncertain due to exact scale of work often unknown before a

technician arrives on site varying technician skill levels

Travel timesUncertain due to weather traffic conditions

Business objectivesResource manager can change business objectives


Complexities

Complex mixture of tasks: different execution target times (appointment/completeBy) different task priorities: Infill tasks - high priority business tasks Wide range in the duration of tasks: 8 mins - several days

Inter task dependencies can be complex coops, assists tasks pre-installation tasks stock point visits, etc

Site access restrictions security access business opening times road closure, etc


Complexities

Geographical complexities diverse (London vs East Wales, etc) Preferred working areas

Skills heterogeneous workforce diverse skill set

Work type and work skill imbalances some geographical areas can be under resourced certain skills can be under resourced

Business Rules


Scale

Scale of individual problems domain dependent

Technicians: 10s to 100s of technicians

Tasks: 100s to 1000s of tasks

Scheduler needs to cope efficiently with all domains


Issues

No realistic forecasting possible! Assumed ‘static’ environment?

Optimised schedules quickly become sub optimal or even infeasible

What is optimality in an dynamic environment? First thing in the morning everything changes !!

(sick leave, new tasks, etc)

Building robust/flexible schedules? Limited applicability Radical changes to the current schedule may be

desired


Needed Automation

Automated data flow from order source systems to job dispatch.

Schedule revision must be automatic and robust.

On line Dispatcher must be able to cope with corrupted schedules.

The real-line monitoring of the location of mobile technicians and their expected completion times is important.


Scheduling Opportunities:

Impact of Personal Digital Assistants on Scheduling

Practice: Mobile phones, laptops, handheld terminals, the

Internet, etc allows to dispatch tasks to mobile workers in real time tasks are (usually) dispatched one by one

Scheduling impact: allows to adjust the schedule to the changed environment allows to correct (some) scheduling decisions made earlier

However, the time available to react to changes is very limited


Reacting to Changes:

Scheduling Opportunities:

Rescheduling

Dynamic scheduling

Real-time scheduling

On-line scheduling

Reactive scheduling


Reactive Scheduling:

In a stochastic environment, such as human

resource scheduling Reactive scheduling

Monitor changes Analyse impact on current schedule Adjust schedule accordingly

schedule repair focused re-optimisation etc.


Reactive Scheduling Tools:

Identify processing bottlenecks Exploit scheduling opportunities Maintain schedule stability and existing process plans. Refine solutions. Repair constraint violations. Summarise solution states for human controllers and

software agents. Dispatch scheduling tasks to field technicians with

respect to current schedule state and customer demand.


Execution cycle

Monitor

Analysis

Revision

Optimise

Execute


TASKFORCE System Overview


TASKFORCE

Developed by BT and employed since 1997.

TASKFORCE supports: Resource Management Operations Management Schedule/Jeopardy Management Progress Management Scheduling & Dispatching


System Overview


Scheduling Architecture

Employed scheduling engines:

Intelligent Appointer

Interrupt Scheduler

Dynamic Scheduler

Dispatcher

Visualisation & What-If Scheduling


Architecture OverviewVisualiser

DS

Pre-scheduler

Optimiser

Interrupt Scheduler

Dispatcher


Schedule Manager



Controller/call centre support tool Heuristic based

find a set of feasible appointment slots based on the current schedule

suggest feasible appointment slots to human controller

controller books appointment slot and associates time windows with the new task

task is sent to schedule manager


Interrupt Scheduler

Automatic Schedule Revision: Reallocation algorithm to support appointment

reservations. A customer requests a technician to attend his

premises between 9am and 12am.

The system can’t find an available resource between these hours but can identify a sequence of reallocations to free a technician to attend the customer.


Dynamic Scheduler: Repair/Optimisation

Responsibilities: Construct high quality start-of-day schedule Rebuild, repair, update & re-optimise while schedule

is being executed

How it works: Build provisional schedule Perform frequent short batch runs to rebuild a

feasible schedule


Dynamic Scheduler: Techniques

Pre-scheduling: Reload and try to rebuild old schedule

Tree Search assigning hard to schedule tasks linked tasks, very long tasks, very important tasks

Optimisation: Stochastic Local Search Simulated Annealing.

Currently looking into more focused techniques such as exploring

large neighbourhoods based on an ejection chain model, Guided

Local Search, etc


Automatic Dispatcher Online and event triggered Rule based system.

If Field Technician request work then the Dispatcher identifies a task for the technician to service.

This invariably results in the need to repair a damaged schedule Schedule analysis will produce state summary reports that

support schedule repair after an unscheduled activity execution.

Focal point Neighbourhood of impact Conflict duration Conflict size


Schedule Visualisation

Compress schedule information and represent it

in a way that can easily be captured by the user Provides the human controller with:

statistics tour task tables Gantt chart map tour representation what-if analysis tools


Schedule Visualisation: Gantt Chart


Schedule Visualisation: Map


Current/Future Work


Dynamic Work Crew Scheduling

Fieldforce activities can often not be carried out

by a single person but need multi skilled crews security reasons (gas, electric, ladder, etc.) activity reasons (two sides of a cable, heavy

equipment) specific equipment (elevator unit, crane, etc)

Examples: Expansion/repair of the telephone network Electricity/gas/water supply to new build homes etc.


Dynamic Work Crew Scheduling

Problems: Complex workpackages (set of linked tasks)

long tasks (2h to a few weeks) many intertask dependencies different configurations possible

Skill matching is a crew skill the sum of its crew member skills?

Task duration If 2 people need 1 hour do 4 people need only 1/2 hour?

How and when to build, combine or break crews in a changing environment?


Incremental Scheduler

Instead of Rescheduling - React to changes immediately Combine scheduling algorithms & dispatcher Basic Idea:

Monitor changes arrival of new tasks resources early or getting delayed tasks moving close to deadlines

React to changes in real time insert new tasks once they arrive move tasks that are getting likely to failure re-optimise parts of the schedule (focused local search)

Intelligent End-to-End Fieldforce Automation

www.apsolve.com

dynamic scheduling in mobile workforce management

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