Generative Design Primer
  • Welcome
  • Introduction to Generative Design
    • Computational Design
    • Generative Design
      • What is Generative Design?
      • Why should I use Generative Design?
      • What goes into a Generative Design Process?
        • Anatomy of each stage
      • Examples of Generative Design
        • MaRs Innovation District of Toronto
        • Furniture Design
        • A Further Analogy
      • Anatomy of a Good Generative Design Process
    • Visual Programming
    • Dynamo
    • Generative Design for Revit and Dynamo
  • Deeper Dive to Generative Design
    • Algorithms
      • What are Algorithms?
      • Generators
      • Evaluators
      • Solvers
    • Optioneering
    • Optimization
      • What is Optimization?
      • Objective Function
      • Constraints
      • Data
      • Defining Goals
    • Genetic Algorithms
      • What is a Genetic Algorithm?
      • Initialization phase
      • Evaluation Phase
      • Selection Phase
      • Crossover Phase
      • Mutation Phase
    • Other Techniques
    • Genetic Algorithm Q&A
  • Hello Generative Design for Revit and Dynamo!
    • Installing Generative Design
    • Setting up a Graph for Generative Design
    • Running Generative Design
    • Visualizing Results in Generative Design
    • Refinery Toolkit
      • Installing the Refinery Toolkit from the Dynamo Package Manager
      • Using the Refinery Toolkit
    • Space Analysis for Dynamo
      • Installing the Space Analysis for Dynamo package from the Dynamo Package Manager
      • Using the Space Analysis Package
    • Using Revit alongside Generative Design
      • Using Data from Revit
      • Remember Node Inputs
      • How to Test Revit Data Capture
      • Detailed Example Workflow
      • Sharing Logic and Results
      • Current Limitations
      • Accessing Generative Design Directly From Revit
  • Sample Workflows
    • Getting Started Workflows
      • Highest Point of a Surface
      • Minimum Volume and Maximum Surface
    • Architectural Workflows
      • Building Mass Generator
      • Building Positioning based on Solar Analysis
      • Office Layout
      • Grid Object Placement in a Room
      • Entourage Placement Exploration
    • MEP Workflows
      • Distributing Spotlights in an Office Space
    • Structural Workflows
    • BIM Workflows
      • Placement of views on sheets
    • Community Examples
      • Guidelines
      • List Of Examples
  • Generative Design in Your Office
    • What Generative Design Can Be Used For?
    • What Generative Design Can’t Be Used For?
    • How to Convince Senior Stakeholders of Using Generative Design?
    • The Role of a Generative Designer
    • Hiring a Generative Designer
  • Next Steps
    • Machine Learning
      • What is Machine Learning?
      • Is Generative Design Machine Learning?
      • Can Machine Learning and Generative Design Work Together?
  • Appendix
    • Glossary
    • Reference Material
    • Need Professional Help?
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  1. Deeper Dive to Generative Design
  2. Algorithms

Evaluators

PreviousGeneratorsNextSolvers

Last updated 5 years ago

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Evaluators (also known as 'discriminators') are fed potential solutions from the generator and assess how good or bad these options are.

For example, in a generative building design, an evaluator might describe the average amount of sunlight that a façade will be exposed to over a one-year time period.

In design, evaluators must be specified mathematically. This is because they have to provide a number for the algorithm to use to discriminate between solutions.

Again, in the simple Dynamo example below, the highlighted nodes are evaluators. They are nodes that query a particular property of the design option - in this case, the volume and surface area of the cuboid.

These evaluators allow the user or program to interrogate each design option and pick the best one based on aspects they want to include e.g. 'maximum volume', 'minimum surface area', etc.