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Pareto Front Optimization

Explore optimal trade-offs between objectives using Pareto Front optimization (Discover mode).

Pareto Front Optimization

Discover mode β€” Explore optimal trade-offs between objectives.

Instead of returning one "best" result, the optimizer finds a set of solutions along the Pareto front β€” the curve where improving one objective necessarily makes another worse. Every point on this front is optimal: no other solution is better on all objectives simultaneously.


When to Use It

  • You are in the exploratory phase and want to understand the trade-off landscape.

  • You do not yet know how to rank or weight your objectives.

  • You want the optimizer to present options so your team can decide later.

What to Expect

Over successive iterations you get a clearer picture of what is achievable. For example: "I can reach 95% yield but only at 85% selectivity, or 90% yield at 92% selectivity."

Example

Optimizing a catalytic reaction with two objectives:

  • Maximize yield

  • Maximize selectivity

Pareto optimization explores the full yield-vs-selectivity trade-off surface so you can see where the sweet spots are.


Good to Know

  • Pareto Front is the default strategy when you add a second objective.

  • Works best with 2 or 3 objectives. For more, consider Weighted Sum or Hierarchy.

  • No parameters to configure β€” it is fully automatic.

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