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Constraint Programming for Industrial Applications H.Simonis

Constraint Programming for Industrial Applications H.Simonis. What is common among. The production of Mirage 2000 fighter aircraft The personnel planning for the guards in all French jails The production of Belgian chocolates The selection of the music programme of a Pop music radio station

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Constraint Programming for Industrial Applications H.Simonis

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  1. Constraint Programmingfor Industrial ApplicationsH.Simonis

  2. What is common among • The production of Mirage 2000 fighter aircraft • The personnel planning for the guards in all French jails • The production of Belgian chocolates • The selection of the music programme of a Pop music radio station • The design of advanced signal processing chips • The print engine controller in Xerox copiers They all use constraint programming to solve their problem

  3. Constraint Programming - in a nutshell • Declarative description of problems with • Variables which range over (finite) sets of values • Constraints over subsets of variables which restrict possible value combinations • A solution is a value assignment which satisfies all constraints • Constraint propagation/reasoning • Removing inconsistent values for variables • Detect failure if constraint can not be satisfied • Interaction of constraints via shared variables • Incomplete • Search • User controlled assignment of values to variables • Each step triggers constraint propagation • Different domains require/allow different methods

  4. Constraint Satisfaction Problems (CSP) • Combinatorial Optimization Problems • Different problems with common aspects • Planning • Scheduling • Resource allocation • Assignment • Placement • Logistics • Financial decision making • VLSI design

  5. Characteristics of these problems • There are no general methods or algorithms • NP-completeness • different strategies and heuristics have to be tested. • Requirements are quickly changing: • programs should be flexible enough to adapt to these changes rapidly. • Decision support required • co-operate with user • friendly interfaces

  6. Techniques behind CLP Predicate logic Unification Non-determinism Logic Programming Constraint propagation Consistency checking Demons CLP tools Artificial Intelligence Operations Research Simplex & Linear programming Integer programming Implicit enumeration Branch & bound Flow algorithms Scheduling methods Graph theory Combinatorics Spatial data structures Equation solving methods Mathematics

  7. Eclipse • Prolog based “constraint toolkit” • Developed first at ECRC, then IC-Parc • Easy to develop new constraint methods • Sets of existing methods/libraries • Basis of problem solvers for PT • Widely used for academic work (> 500 sites)

  8. CLP tool history logic based Other base language ALICE Prolog III CLP(R) CHIP CHIP SEPIA CAL SNI Prolog Decision Power Charme BNR Pecos cc(FD) Charme Object Prolog IV CHIP V4 Solver Eclipse CHIP lib Claire Oz CHIP V5

  9. Classification of CLP solvers • Computation domain • Deterministic solver (search under user control) • Efficient methods • More than one application • Complete/incomplete • decide satisfiability of constraint sets • complexity of solver/ simplicity of programs • Methods • syntactic: domain independent • semantic: domain dependent

  10. Constraint system structure Constraints Complete solver Incomplete solver Interval Finite domains Boolean Rational Others Boolean Others Control Constraint solver Domain concept Heuristics Back tracking Meta- heuristics semantic syntactic Variable selection Value selection numerical symbolic equality inequality disequality element cumulative diffn cycle among sequence

  11. Computation domains • Finite domains • Linear arithmetic • Boolean • Pseudo Boolean • Non-linear arithmetic • Intervals • Sets, sequences, lists the initial domains in Prolog III, CLP(R) and CHIP

  12. Incomplete finite domain solver • Domain • finite sets of values • subsets of natural numbers • Need for enumeration • Classification criteria • constraint granularity • richness of constraint sets • propagation results • user definable constraints/control • Methods • explicit domain representation • bound propagation/ removal of interior values • heuristics based on domains

  13. Need for global constraints 1 X X in {2,3} Y 2 Y in {2,3}  U in {1,2,3,4} Z 3 Z in {1,3} U 4 local reasoning, no action global reasoning, detect implications by bi-partite matching

  14. Global constraints • Work on sets of variables • Global conditions, not local constraints • Semantic methods • Operations Research • Spatial algorithms • Graph theory • Network flows • Building blocks (high-level constraint primitives) • Multi-purpose • As general as possible • Usable with other constraints • Very strong propagation • Acceptable algorithmic complexity

  15. Constraint morphology precedence diffn cumulative sequence cycle case among alldifferent setup disjunctive permutation prod/cons \= >=, distance atmost, atleast circuit element Different Order Resource Tour Dependency

  16. Search tree visualization • Generation of search tree representation at run-time • Shows parent child relation, failed sub-trees, success nodes • In examples here • leaf failure nodes suppressed • failure trees not collapsed • Interface a set of simple meta-call predicates • Supported by work in DISCIPL Esprit project • Declarative debugging • Visualization of constraint programming results • Understand behaviour of different strategies

  17. Search tree tool Menubar Panel Tree view Other Views, here domain state Info Area

  18. Example of tree search credit([X1..X10],8, 10, my_delete, my_indomain,4,part(1,2)),

  19. Success Stories for Constraint Logic Programming COSYTEC – IC-Parc

  20. Hardware design Compilation Financial problems Placement Cutting problems Stand allocation Air traffic control Frequency allocation Network configuration Product design Production step planning Production sequencing Production scheduling Satellite tasking Maintenance planning Product blending Time tabling Crew rotation Aircraft rotation Transport Personnel assignment Personnel requirement planning Overview

  21. Five central topics • Assignment • Parking assignment • Platform allocation • Network Configuration • Scheduling • Production scheduling • Project planning • Transport • Lorry, train, airlines • Personnel assignment • Timetabling, Rostering • Train, airlines

  22. Stand allocation • HIT (ICL Hong-Kong) • assign ships to berths in container harbour • developed with ECRC’s version of CHIP • then using DecisionPower (ICL) • first operational constraint application (1989-90) • APACHE (COSYTEC) • stand allocation for airport • Refinery berth allocation (ISAB) • where to load/unload ships in refinery

  23. AIR FRANCE - APACHE • Stand allocation system • Originally developed for Air France, CDG2 • Packaged for large airports • Complex constraint problem • Technical & operational constraints • Incremental re-scheduler • Cost model • Max. nb passengers in contact • Min. towing, bus usage • Benefits and status • Quasi real-time re-scheduling • KAL, Turkish Airlines

  24. Network configuration • RiskWise (PT) • Locarim (France Telecom, COSYTEC) • cabling of building • Planets (UCB, Enher) • electrical power network reconfiguration • Load Balancing in Banking networks (ICON) • distributed applications • control network traffic • Water Networks (UCB, ClocWise)

  25. RiskWise • Traffic analysis/optimization for IP networks • Find out end-to-end communication flows in the network of an ISP • Suggest changes in network which optimize investment • Handle incomplete data

  26. Production scheduling • Atlas (Monsanto) • Herbizide production • Cerestar (OM Partners) • Glucose production • KAPSS (Mitsubishi Chemical) • offset printing plates • Trefi Metaux (Sligos) • heavy industry production scheduling • Michelin • rubber blending, rework optimization

  27. DASSAULT - PLANE • Assembly line scheduling • developed by Dassault Aviation for Mirage 2000 Jet/ Falcon business jet • Two user system • production planning 3-5 years • commercial what-if sales aid • Optimisation • requirement to balance schedule • minimise changes in production rate • minimise storage costs • Benefits and status • replaces 2 week manual planning • operational since Apr 94 • now used in US for business jets

  28. FINA - FORWARD • Oil refinery production scheduling • joint development by TECHNIP and COSYTEC • incorporates ELF FORWARD LP tool • Schedules daily production • crude arrival -> processing -> delivery • design, optimize and simulate • Product Blending • explanation facilities • handling of over-constrained problems • Status • generic tool developed in 240 man days • operational since June 94 • Operational at FINA, ISAB, BP

  29. Transport • By Air • AirPlanner (PT) • Daysy (Lufthansa) • Pilot (SAS) • By Road • Wincanton (IC-Parc) • TACT (SunValley) • EVA (EDF) • By Rail • CREW (Servair) • COBRA (NWT)

  30. EDF- EVA • Transportation of nuclear waste • developed by GIST + COSYTEC • plans evacuation and transport for 54 sites • Constraints • availability of transport vehicles and vessels • no and capacity of storage tanks • compatibility of waste to vessels • size of convoy, time • Status • operational since Oct 94 • 6 month plan in 5 minutes

  31. SERVAIR - CREW • Crew rostering system • assign service staff to TGV train timetable • joint implementation with GSI • Problem solver • generates tours/cycles • assigns skilled personnel • Constraints • union, physical, calendar • Status • operational since Mar 1995 • cost reduction by 5%

  32. Personnel Planning • RAC (IC-Parc) • OPTISERVICE (RFO) • Shifter (ERG Petroli) • Gymnaste (UCF) • MOSAR (Ministère de la JUSTICE)

  33. RFO - OPTI SERVICE • Assignment of technical staff to tasks • overseas radio broadcasting network - Radio France Outre-mer • joint development by GIST and COSYTEC • 250 journalists and technicians • Features • schedule manually, check, automatic • rule builder to specify cost formulas • Optimization • minimize overtime, temporary staff • compute cost of schedule • Status • operational since 1997 • installed worldwide in 8 sites • Now used for other companies • TSR • Canal+

  34. Case Study: Semi Process Industry

  35. ATLAS (Monsanto, Antwerp) • Scheduling system in chemical factory • herbicide manufacturing and packaging • integrated inventory control system • Life system • first phase operational since July 93 • second phase operational since March 94 • major revision in 98 (SAP connection) • Developed jointly by • OM Partners (Antwerp) • COSYTEC • Multi-user PC/UNIX system • multiple schedulers • co-operative behavior

  36. Manufacturing Process Formulation Packaging intermediate products Outside G finished products Dr Holding area F1 L1 raw material L2 F2 L3 Gr L4

  37. Users Schedulers Factory Formulation Packaging Purchasing Production Dynamic Scheduling Environment Sales forecast (6 month horizon) Orders (delay 1day to 4 weeks) Stock level update planned/realized Data base Arrivals (lead time 3 weeks) Production Schedule Shop floor data

  38. Scheduling Process Priority orders Users Schedulers Old schedule Fine tuning of sequence Factory Formulation Packaging medium/long term impact Purchasing Production Production problems Visualization of schedule (stock level, delays, down times...) New Schedule short term reaction Re-scheduling Formulation Re-scheduling Packaging

  39. IBM - VMAntwerp IBM - MVSSASBrussels Architecture X 25 Scheduling CHIP USA ORACLE Users PC / XWindowsGUI HP UNIX Purchasing Planner Factory SchedulerFormulation Scheduler Packaging Production manager Ethernet

  40. The system • Connection to other systems • Data download/upload from/to local and remote mainframes • End-user connection via PCs • Data base • Local on UNIX machine • ORACLE SQL standard • Forms/reports facilities • Multi-user tool • Multiple schedulers for parts of production • Inventory control • Production • Multiple scenarios; one schedule

  41. Constraint solver • Constraints handled • Machine choice • Sequence/ machine dependent set-up • Manpower limits • Component consumer constraints • Finished product producer constraint • Producer/consumer constraints for intermediate products • Production planning for batch part • Number of batches for intermediate products • Optimum batch sizing • Limited stock levels

  42. cumulative The Cumulative global constraint • Cumulative constraint • Resource limits over periods of time • Upper/lower limits • Soft/hard limits • Gradual constraint relaxation • Application • Resource restrictive scheduling, producer consumer constraints, disjunctive schedule, manpower constraints, overtime

  43. Cumulative • Methods • obligatory parts • task intervals • available space • many more (25000 lines of C code) • Concepts • one constraint may be used for different purposes

  44. diffn The Diffn global constraint • Diffn constraint • non overlapping areas on n-dimensional rectangles • distances between rectangles • limit use of areas • relaxation • Application • layout, packing, resource assignment, setup, distribution planning, time-tabling

  45. Diffn • Methods • obligatory parts • region intervals • max flow on assignment • available space • many others (32000 lines of C code) • Concepts

  46. cycle The Cycle global constraint • Cycle constraint • Finds cycles in directed graphs with minimal cost • Assign resources, find compatible start dates • Applications • Tour planning, personnel rotation, distribution problems, production sequencing

  47. Cycle • Methods • connected components • bi-partite matching • non-oriented graph concepts • shortest/longest paths • micro-rules • many others (38000 lines of C code) • Concepts

  48. ATLAS - Summary • End-user system • Direct manipulation • Constraints not visible to user • Changes/strategies expressed via interface • Complex scheduling problem • Real-life, not pure problem • Interaction/conflicts between constraints • Incremental expression with constraints • Development effort (250 days) • Integration • Data base reporting • Graphical interface • Problem solver

  49. The CHIP system: Constraints and ... Application XGIP QUIC Objects Solvers CHIP Application CHIP CHIP++ EMC/CLIC

  50. Behind the scene • CHIP kernel 175000 lines • Prolog 15000 • Core Constraints 20000 • Global Constraints 140000 • Interfaces 5000 lines • CLIC • EMC • QUIC • XGIP graphics 20000 lines • Graphics libraries 17000 lines

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