> For the complete documentation index, see [llms.txt](https://www.generativedesign.org/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://www.generativedesign.org/02-deeper-dive/02-03_optimization/02-03-03_constraints.md). # Constraints ![](/files/-LrPm4HMsOaw4omeOpPe) A constraint is a condition that the solution of an optimization problem must satisfy. In the table example we saw earlier, the constraints could be: * 'the table must have four legs' * 'the table must be at least 50cm wide' * 'the table may be no more than 1m tall', or * 'the table cannot be blue'. Constraints give a model its realism; they ensure that a solution only includes realistic values or values that the user knows are critical to the design brief. If a model is unconstrained, it's likely to return absurd results that aren’t useful, for example, here it could be a circular table that is three metres high with a single leg that balances on a point. Constraints are vital because they ensure that a generative design algorithm outputs something realistic and reasonable. --- # Agent Instructions This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com. ## Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question. Perform an HTTP GET request on the current page URL with the `ask` query parameter, and the optional `goal` query parameter: ``` GET https://www.generativedesign.org/02-deeper-dive/02-03_optimization/02-03-03_constraints.md?ask=&goal= ``` `ask` is the immediate question: it should be specific, self-contained, and written in natural language. `goal` is optional and describes the broader end goal you are ultimately trying to accomplish on behalf of the user. GitBook uses it to tailor the answer towards what is most useful for that goal. The response will contain a direct answer to the question and relevant excerpts and sources from the documentation. Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.