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mip-solver-and-solution-audit
Operational workflow for hard integer-programming optimization tasks: selecting an installed solver, preserving solver/incumbent certificates, extracting feasible schedules, recomputing metrics from final outputs, and writing consistent reports. Use when a task requires a MIP, solver status, objective value, bound, gap, formulation write-up, or benchmark output files.
tasks/exam-block-sequencing/environment/skills/mip-solver-and-solution-audit/SKILL.md
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# MIP Solver and Solution Audit
## Core principle
A valid optimization submission has one final solution, one set of recomputed
metrics, and one truthful solver report. The solver objective, written output,
metrics file, and explanation must all refer to the same final solution.
Feasible does not mean optimal. A time-limited MIP solve may return a useful
incumbent without proving optimality. Report that distinction clearly.
## Solver discovery
For Python optimization tasks, test installed solver packages before concluding