Dynamic Scheduling in Mobile Workforce Management

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Dynamic Scheduling in Mobile Workforce Management

• Ralf Keuthen

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Contents

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

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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 Telecoms Brightstar business incubator
  initiative in April 2003.
• a.p.solves planning and scheduling products
  primarily support the management of mobile
  workers via Personal Digital Assistants and
  mobile telephony.

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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)

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Example Mobile Workforce at British Telecom

• BT Customer Access
• a.p.solves TASKFORCE products currently schedule
  BTs 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.

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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

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Organisation How it works
Customer Service
Work allocation and visualisation
Dispatch work to technicians

• Handheld terminal
• Laptop
• Mobile

• Call Centre
• Network Service

TASKFORCE
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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

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Workforce Management From a Scheduling Point of
View
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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.

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Main Objectives

• Right 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

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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

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Issues

• Dynamics/Uncertainties/Complexities of problem
• Scale
• The need for a totally automated, online, system.

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Dynamics

• Tasks
• The company and its customers can
• request
• cancel
• amend tasks (at all time!!)
• Resources
• Availability subject to last minute changes
• personal absence, sick leave, etc
• changes to task completion times
• vehicle breakdown

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Uncertainties

• Duration of tasks
• Uncertain due to
• exact scale of work often unknown before a
  technician arrives on site
• varying technician skill levels
• Travel times
• Uncertain due to
• weather
• traffic conditions
• Business objectives
• Resource manager can change business objectives

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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

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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

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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

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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

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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.

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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

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Reacting to Changes

• Scheduling Opportunities
• Rescheduling
• Dynamic scheduling
• Real-time scheduling
• On-line scheduling
• Reactive scheduling

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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.

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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.

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Execution cycle
Monitor
Analysis
Execute
Optimise
Revision
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TASKFORCE System Overview
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TASKFORCE

• Developed by BT and employed since 1997.
• TASKFORCE supports
• Resource Management
• Operations Management
• Schedule/Jeopardy Management
• Progress Management
• Scheduling Dispatching

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System Overview
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Scheduling Architecture

• Employed scheduling engines
• Intelligent Appointer
• Interrupt Scheduler
• Dynamic Scheduler
• Dispatcher
• Visualisation What-If Scheduling

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Architecture Overview
Visualiser
Intelligent Appointer
DS
Optimiser
Dispatcher
Interrupt Scheduler
Pre-scheduler
Schedule Manager
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Intelligent Appointer

• 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

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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 cant find an available resource
  between these hours but can identify a sequence
  of reallocations to free a technician to attend
  the customer.

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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

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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

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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

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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

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Schedule Visualisation Gantt Chart
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Schedule Visualisation Map
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Current/Future Work
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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.

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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?

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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)

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www.apsolve.com

Intelligent End-to-End Fieldforce Automation