Individual skill
cuopt-multi-objective-exploration
Trace, complete, and interpret the Pareto frontier across competing objectives using repeated single-objective cuOpt solves (weighted-sum and ε-constraint).
skills/cuopt-multi-objective-exploration/SKILL.md
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- multi-objective Declared skill tag
- pareto Declared skill tag
- epsilon-constraint Declared skill tag
- tradeoff Declared skill tag
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# Multi-Objective Exploration
cuOpt optimizes **one** objective per solve. Many real problems have several objectives that pull against each other — cost vs. service level, return vs. risk, makespan vs. overtime, distance vs. vehicle count. A single solve answers "what's optimal *for one particular weighting*," but it hides the tradeoff the user actually needs to see.
This skill turns a sequence of single-objective cuOpt solves into a **Pareto frontier** — the set of solutions where you can't improve one objective without giving up another — and gives the discipline to read it. It adds no solver features; it orchestrates the LP / MILP / QP solves already covered by the formulation and API skills.
## When this applies
Reach for this workflow when the problem has **two or more objectives with no agreed-upon weighting**, signalled by language like:
- "balance X and Y", "trade off", "as cheap as possible *without* hurting service"