Decision Optimization

IBM® Decision Optimization for Watson Studio allows you to run optimization models in Watson Studio, with a user-friendly environment in which you can combine optimization with data science and machine learning. IBM® Decision Optimization gives you access to IBM's industry-leading solution engines for mathematical programming and constraint programming.

IBM® Decision Optimization for Watson Studio provides you with a model builder interface to facilitate workflow. Here you can:

  • Select and edit the data relevant for your optimization problem
  • Create, import, edit and solve Python models in the Decision Optimization model builder (Beta version) or in Jupyter notebooks
  • Create, import, edit models using your data and natural language expressions with the Modeling Assistant (Beta version) and solve them
  • Create, import, edit and solve OPL models in the Decision Optimization model builder
  • Run optimization models in the Decision Optimization model builder (Beta version) or in Jupyter notebooks
  • Investigate and compare solutions for multiple scenarios
  • Easily create tables, charts and notes to visualize data and solutions, using widgets provided in the Visualization Editor
  • Deploy models using Watson Machine Learning

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