You are previewing Optimization and Decision Support Design Guide: Using IBM ILOG Optimization Decision Manager.
O'Reilly logo
Optimization and Decision Support Design Guide: Using IBM ILOG Optimization Decision Manager

Book Description

Today many organizations face challenges when developing a realistic plan or schedule that provides the best possible balance between customer service and revenue goals. Optimization technology has long been used to find the best solutions to complex planning and scheduling problems. A decision-support environment that enables the flexible exploration of all the trade-offs and sensitivities needs to provide the following capabilities:

  • Flexibility to develop and compare realistic planning and scheduling scenarios

  • Quality sensitivity analysis and explanations

  • Collaborative planning and scenario sharing

  • Decision recommendations


This IBM® Redbooks® publication introduces you to the IBM ILOG® Optimization Decision Manager (ODM) Enterprise. This decision-support application provides the capabilities you need to take full advantage of optimization technology. Applications built with IBM ILOG ODM Enterprise can help users create, compare, and understand planning or scheduling scenarios. They can also adjust any of the model inputs or goals, and fully understanding the binding constraints, trade-offs, sensitivities, and business options.

This book enables business analysts, architects, and administrators to design and use their own operational decision management solution.

Please note that the additional material referenced in the text is not available from IBM.

Table of Contents

  1. Front cover
  2. Notices
    1. Trademarks
  3. Preface
    1. The team who wrote this book
    2. Now you can become a published author, too!
    3. Comments welcome
    4. Stay connected to IBM Redbooks
  4. Part 1 Business concepts, architecture, and design
  5. Chapter 1. Context for optimization and analytic decision support
    1. 1.1 Can we have your attention please
    2. 1.2 What is optimization
      1. 1.2.1 Analytics and optimization
      2. 1.2.2 What optimization can achieve
      3. 1.2.3 How do I recognize an optimization application
      4. 1.2.4 How optimization works
    3. 1.3 How can optimization benefit your organization
      1. 1.3.1 Example: Airline crew recovery
      2. 1.3.2 Example: Securities transactions settlements
      3. 1.3.3 Example: Power plant dispatching
      4. 1.3.4 Example: Semiconductor manufacturing
    4. 1.4 How can you make it happen
    5. 1.5 Why should your organization consider analytic decision support
  6. Chapter 2. Introducing the ODM Enterprise solution
    1. 2.1 From optimization model to business application
    2. 2.2 The ContainerYard: An ODM Enterprise application example
      1. 2.2.1 Supply chain process
      2. 2.2.2 Planning process
      3. 2.2.3 Solution: An ODM Enterprise-based software application
      4. 2.2.4 Planning scenarios
    3. 2.3 Application concepts and parts of an ODM Enterprise solution
      1. 2.3.1 ODM Studio: The planning cockpit
      2. 2.3.2 Deployment architectures
    4. 2.4 Optimization concepts and parts of an ODM Enterprise solution
      1. 2.4.1 Optimization model
      2. 2.4.2 Optimization engines
      3. 2.4.3 CPLEX Optimization Studio
    5. 2.5 Roles and expertise
      1. 2.5.1 Client roles
      2. 2.5.2 Provider roles
    6. 2.6 Advantages of ODM Enterprise solutions
    7. 2.7 Conclusion
  7. Chapter 3. ODM Enterprise architecture
    1. 3.1 Key ODM Enterprise concepts
      1. 3.1.1 Model
      2. 3.1.2 ODM Enterprise IDE versus ODM Studio
      3. 3.1.3 Scenario
      4. 3.1.4 Workspace
      5. 3.1.5 Scenario Repository
      6. 3.1.6 Goals
      7. 3.1.7 Requirements
      8. 3.1.8 Rules
      9. 3.1.9 Input data and solution views
      10. 3.1.10 Decision process configuration
      11. 3.1.11 Solve
      12. 3.1.12 Deployment
      13. 3.1.13 Collaboration
    2. 3.2 ODM Enterprise architecture
      1. 3.2.1 Optimization Server
      2. 3.2.2 Data Server
      3. 3.2.3 ODM Studio
    3. 3.3 ODM Enterprise API
    4. 3.4 Domain Object Model (DOM)
    5. 3.5 Data architecture
      1. 3.5.1 Scenario Repository
      2. 3.5.2 Importing data
      3. 3.5.3 Exporting data
      4. 3.5.4 Application and Jobs database
    6. 3.6 Scalability and load balancing
    7. 3.7 High availability
    8. 3.8 Security model
      1. 3.8.1 Simple authentication system
      2. 3.8.2 Custom authentication system
    9. 3.9 Conclusion
  8. Chapter 4. Transforming business requirements into an ODM Enterprise application
    1. 4.1 ODM Enterprise development process
      1. 4.1.1 ODM Enterprise development flow
      2. 4.1.2 ODM Enterprise IDE
    2. 4.2 Building the ContainerYard application
      1. 4.2.1 Analyzing requirements and defining application scope
      2. 4.2.2 Defining the data model
      3. 4.2.3 Creating a prototype without optimization
      4. 4.2.4 Creating a prototype with optimization
      5. 4.2.5 Deploying the application
    3. 4.3 Conclusion
  9. Chapter 5. Solution design and management
    1. 5.1 ODM Enterprise editions
      1. 5.1.1 ODM Enterprise Developer Edition
      2. 5.1.2 ODM Enterprise Optimization Server
      3. 5.1.3 ODM Enterprise Optimization Engine
      4. 5.1.4 ODM Enterprise Data Server
      5. 5.1.5 ODM Enterprise Client Edition
      6. 5.1.6 ODM Enterprise Planner Edition
      7. 5.1.7 Staging database
    2. 5.2 Deployment and system design options
      1. 5.2.1 Common ODM Enterprise deployment configurations
      2. 5.2.2 Individual deployment
      3. 5.2.3 Enterprise with local optimization deployment
      4. 5.2.4 Enterprise deployment
      5. 5.2.5 Other considerations while you are designing the solution
    3. 5.3 Input data and processing
    4. 5.4 Conclusion
  10. Part 2 Customer use cases
  11. Chapter 6. Case study: An insurance company
    1. 6.1 Company overview
    2. 6.2 Business problem
    3. 6.3 Business requirements
      1. 6.3.1 Non-functional requirements
      2. 6.3.2 User interface requirements
    4. 6.4 Optimization problem
      1. 6.4.1 Choices
      2. 6.4.2 Targets
      3. 6.4.3 Limits
      4. 6.4.4 Data
    5. 6.5 Solution development
      1. 6.5.1 Architecture
      2. 6.5.2 Data requirements
    6. 6.6 Optimization
    7. 6.7 Conclusion
  12. Chapter 7. Case study: A manufacturing company
    1. 7.1 Business context
    2. 7.2 Business problem
      1. 7.2.1 Old process issues
      2. 7.2.2 Solution
    3. 7.3 Business requirements
      1. 7.3.1 Assignment
      2. 7.3.2 Capacity planning
      3. 7.3.3 Capacities, overload, and extension
      4. 7.3.4 Non-functional requirements
    4. 7.4 Optimization problem
      1. 7.4.1 Assignment
      2. 7.4.2 Capacity planning
    5. 7.5 Solution
      1. 7.5.1 Solution architecture
      2. 7.5.2 User interface
      3. 7.5.3 Implementation project
    6. 7.6 Conclusion
  13. Part 3 Appendixes
  14. Appendix A. IBM solution landscape for analytics, optimization, and decision support
    1. ODM Enterprise overview
    2. IBM ILOG CPLEX Optimization Studio overview
    3. SPSS
    4. Cognos
    5. WebSphere ILOG Rules
    6. Summary
  15. Appendix B. Troubleshooting
    1. General concepts and guidelines
    2. Troubleshooting tips
  16. Appendix C. Additional material
    1. Locating the web material
    2. Using the web material
  17. Glossary
  18. Related publications
    1. IBM Redbooks
    2. Education
    3. Other publications
    4. Online resources
    5. Help from IBM
  19. Back cover