InventoryOptimization
Task 10 / 47
disruption_eoqd
EOQ-style lot-sizing under supply disruptions: optimize order quantities and reorder points when supply availability is stochastic, minimizing long-run expected cost blending holding, shortage, and ordering. It extends classical EOQ with resilience-motivated uncertainty modeling.
Model leaderboard
Updated v1 results · 2026-09-15 · raw score, higher is better.
| # | Participant | Raw score | Medal |
|---|---|---|---|
| 1 | Claude Opus 4.6 | 0.6473 | Gold |
| 2 | Gemini 3.1 Pro Preview | 0.639 | Silver |
| 3 | DeepSeek V3.2 | 0.6381 | Bronze |
| 4 | Grok 4.20 | 0.6359 | — |
| 5 | Seed 2.0 Pro | 0.6321 | — |
| 6 | GLM-5 | 0.6303 | — |
| 7 | Qwen3 Coder Next | 0.6225 | — |
| — | GPT-5.4 | No valid score | — |
Framework results · original paper
Historical results from the original evaluators · normalized score (0–100).
| # | Participant | Score |
|---|---|---|
| 1 | Claude Opus 4.6 + OpenEvolve | 100.0 |
| 2 | GPT-OSS + ABMCTS | 65.0 |
| 3 | GPT-OSS + ShinkaiEvolve | 42.9 |
| 4 | GPT-OSS + OpenEvolve | 42.9 |
| 5 | Claude Opus 4.6 + ABMCTS | 38.4 |
| 6 | Claude Opus 4.6 + ShinkaiEvolve | 0.0 |
Model results use the updated scores and medal thresholds. No valid score earns zero medal credit. Historical framework scores use the original evaluators and have not been updated alongside the model results.