1 / 43

Dynamic Scheduling in Mobile Workforce Management

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

mercer
Télécharger la présentation

Dynamic Scheduling in Mobile Workforce Management

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript


  1. Dynamic Scheduling in Mobile Workforce Management Ralf Keuthen

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

  3. 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.

  4. 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)

  5. 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.

  6. 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

  7. Organisation: How it works Customer Service Work allocation and visualisation Dispatch work to technicians • Handheld terminal • Laptop • Mobile • Call Centre • Network Service TASKFORCE

  8. 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

  9. Workforce Management: From a Scheduling Point of View

  10. 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.

  11. 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

  12. 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

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

  14. 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

  15. 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

  16. 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

  17. 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

  18. 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

  19. 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

  20. 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.

  21. 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

  22. Reacting to Changes: Scheduling Opportunities: • Rescheduling • Dynamic scheduling • Real-time scheduling • On-line scheduling • Reactive scheduling

  23. 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.

  24. 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.

  25. Execution cycle Monitor Execute Analysis Optimise Revision

  26. TASKFORCE System Overview

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

  28. System Overview

  29. Scheduling Architecture Employed scheduling engines: • Intelligent Appointer • Interrupt Scheduler • Dynamic Scheduler • Dispatcher • Visualisation & What-If Scheduling

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

  31. 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

  32. 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.

  33. 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

  34. 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

  35. 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

  36. 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

  37. Schedule Visualisation: Gantt Chart

  38. Schedule Visualisation: Map

  39. Current/Future Work

  40. 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.

  41. 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?

  42. 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)

  43. www.apsolve.com Intelligent End-to-End Fieldforce Automation

More Related