Claude Haiku 5.5 (effort default (no --effort flag) · thinking on) on Optimal single-machine job sequence (weighted tardiness with precedence)

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  "result": "I wrote `solve.py` and it produces `answer.json` for the fixture: sequence of 18 jobs with total weighted tardiness **462**. The solver is an exact subset DP, so the result is the true optimum, not a heuristic.\n\n**How it works**\n- A set of jobs scheduled first has a fixed completion time (`start + sum of p`), so appending job j costs `w_j * max(0, C - d_j)` regardless of the order inside the set.\n- Jobs are only appended once all their predecessors (transitive closure of the precedence pairs) are already in the set, which enforces precedence.\n- The optimal sequence is recovered from parent pointers. `main()` asserts that the output is a permutation, respects every precedence pair, and that the recomputed objective matches the reported value.\n\n**Verification**\n- **Brute force:** on 300 random instances with 2\u20138 jobs, random start times, and random precedence sets, the DP matched the minimum over all permutations (0 mismatches). Each returned sequence was also checked for precedence and objective.\n- **Timing:** a 21-job instance with no precedence (the worst case, 2\u00b2\u00b9 states) takes about 4.7 s. A 21-job instance with 15 precedence pairs takes 0.3 s. Both are well under the 90 s limit.\n- The fixture runs in about 0.16 s.\n\n**Files:** `./usecase-runner/runs/m07-claude-haiku/work/solve.py` and `answer.json`. The test script lives in `/tmp/chk`, outside the work directory. The directory is not a git repository, so I did not commit anything.",
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