/optimize-design-under-budget

name: optimize-design-under-budget
description: "Given cost per run and resource budget, choose the most information-efficient feasible design while preserving essential validity constraints."

optimize-design-under-budget

Purpose

Given cost per run and resource budget, choose the most information-efficient feasible design while preserving essential validity constraints.

Input contract

required: [candidate_designs, run_costs, resource_budget, validity_constraints]
optional: [evidence, assumptions, prior_results]
constraints: [use named scientific objects; retain provenance and missingness; $\alpha$ = 0.05 and power = 0.8 where applicable]

Procedure

1. Validate the typed inputs and state the decision this operation must support. 2. Apply the declared operation to the named object; record intermediate values that affect interpretation. 3. Check boundary conditions and counterexamples, then emit the result with uncertainty and source links.

Output contract

produces: [optimize_design_under_budget_result, evidence_trace, uncertainties]
delta_fields: [evidence_updates, uncertainties]

Quality gates

• Inputs are named scientific objects with compatible schemas.
• Every material result has a derivation or source reference.
• Fixed statistical criteria remain exact where applicable: $\alpha$ 0.05 and power 0.8.

Failure and counterexamples

Return a failed operation with the violated precondition when inputs are incomplete, assumptions are unsupported, or a counterexample defeats the result.

Provenance map

• intermediate: experiment-execution/budget-constrained-design [tactic]