Stop arguing from one metric at a time.
Multi-Objective Pareto Ranker
Bring multiple decision axes into a single Pareto view so the tradeoffs between battery performance, confidence, and supply risk are visible before a team over-optimizes the wrong variable.
Key outcomes
What goes in
Inputs this feature expects
- A candidate set from search, screening, or simulation
- Objective weights or constraints when a program has hard limits
- Capacity, voltage, conductivity, coulombic efficiency, energy, confidence, and supply-risk signals already joined in Lattice Graph
What comes out
Outputs your team can act on
- A frontier view of non-dominated candidate options
- Explicit tradeoffs between the metrics that matter
- A traceable ranking for review and portfolio selection
Workflow
How teams use Multi-Objective Pareto Ranker
Define the decision axes
Choose the objectives that matter for the battery program, such as capacity, voltage, or supply risk.
Project the candidate set
Lattice Graph computes the frontier and highlights the non-dominated choices.
Select by tradeoff, not instinct
Teams can make choices with the actual compromises visible in one place.
Best fit
Where this feature fits best
- Portfolio selection where multiple constraints matter
- Tradeoff reviews between technical and commercial teams
- Any ranking process that has outgrown single-metric sorting
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