Ilog solver directions
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ILOG Solver Directions. Laurent Perron ILOG SA. Outline. Constraint Programming, a powerful technology The CP suite in ILOG CP faces new challenges Recent Technical Advances. Constraint Programming, a Powerful Technology. I hope this will be demonstrated by the workshop

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ILOG Solver Directions

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Ilog solver directions

ILOG Solver Directions

Laurent Perron

ILOG SA


Outline

Outline

  • Constraint Programming, a powerful technology

  • The CP suite in ILOG

  • CP faces new challenges

  • Recent Technical Advances


Constraint programming a powerful technology

Constraint Programming, a Powerful Technology

  • I hope this will be demonstrated by the workshop

  • CP is a robust technology with a past of successful applications

    • Some famous academics success in the OR community (10 teams problem closed easily)

    • A large collection of deployed industrial applications based on Constraint Programming


Cp strengths

CP Strengths

  • A high level modeling language allows for a rich and accurate representation of the model

  • Domain expertise is captured through a rich search language

  • Special techniques (decomposition, LNS, repair…) allows the tackling of large and difficult problems

  • “A clever tool for clever people”


Cp weaknesses

CP weaknesses

  • A high level modeling language allows for a rich and accurate representation of the model

  • Domain expertise is captured through a rich search language

  • Special techniques (decomposition, LNS, repair…) allows the tackling of large and difficult problems

  • You need clever people to use this clever tool


Ilog cp suite

ILOG CP Suite

  • ILOG Solver

    • Generic CP System

  • ILOG Scheduler

    • Detailed Scheduling Specialization

  • ILOG Dispatcher

    • Vehicule Routing and Disptaching Specialization

  • ILOG Configurator

    • Configuration System


Ilog cp market

ILOG CP Market

  • ILOG CP Market is defined by

    • ILOG Consultants

    • Big ISV

    • Specialized Solution Vendors

    • Technical Consulting Companies

    • Big Companies with Dedicated R&D

  • This is not a huge market

  • We want to enlarge our market


Cp meets new challenges

CP Meets New Challenges

  • To reach our goals, CP should be improved

  • At the evaluation phase

    • Easier to use tools

    • Rapid results

    • Low coding effort

  • At the implementation phase

    • Low technology profile

  • At the maintenance phase

    • The application should improve with time


New rules for tools evaluation

New Rules for Tools Evaluation

  • People are not very technical

    • Maybe one week of training

  • They may have a limited OR background

    • The know basic OR rules about modeling

  • They may not be Computer Science experts

    • The cp system should be easily integrated/documented

    • Maybe not keen with compilers and library


News rules for evaluation 2

News Rules for Evaluation (2)

  • Evaluation Phase is Limited in time

  • IT is made against other competing techniques

    • And sometimes against internal tools

  • We need to achieve something soon

    • Even if the problem is over-constrained

    • Even if the data are dirty

    • Even if the model is naive


New rules for application development

New Rules for Application Development

  • The IT guy is not the OR Expert

  • The code will not evolve

  • The time devoted to Optimization is usually limited

  • Users will need guidance

    • Why this doesn’t work?

  • Users expect performance to improve with time

    • Without code evolution


Usability

Usability

  • To be effective, a CP solution consists of

    • A good model

    • A clever search part

  • We would like to remove the need for search part

  • At least for small problems, typically the one encountered in the evaluation phase


Robustness

Robustness

  • Different logically equivalent formulations can lead to different runtime performances

    • Expand a global constraint into smaller subparts

  • This imply that getting a good model is an art

  • We do not believe this cannot be

  • The CP Solver should detect these cases and reformulate the model

  • Users do not know about different level of propagation


Evolution of the code

Evolution of the Code

  • In the past, to use a new technology, a new constraint or a new search construct was implemented

  • Users had to rewrite their code in order to benefit from it

  • And new users had to learn more each time


Interactivity

Interactivity

  • Users want Explanation

    • And useful explanations

  • Users want Solutions

    • Even with over-constrained problems

    • Along with explanations of why some constraints are not part of the solution


Ilog solver directions1

ILOG Solver Directions

  • Default Search

  • Model Reinforcement

  • Constraint Aggregation

  • Various work on robustness

    • Better constraints (without filtering levels)

    • No pathological cases

    • No slow propagation

  • Explanations and Solver Anyway


Ilog cp directions

ILOG CP Directions

  • There is a new suite of optimization tools in ILOG

  • ILOG Plant Power Ops for production planning and scheduling

  • ILOG Transport Power Ops for routing and dispatching

  • ILOG Fab Power Ops for semi conductor industry


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