InventoryOptimization
Task 12 / 47
general_meio
General-topology multi-echelon inventory optimization (MEIO) with simulation-based expected cost objectives over stochastic demand, possibly including non-tree networks. Policy search targets base-stock–like parameters under sample-path evaluation—realistic MEIO engineering beyond trees.
Model leaderboard
| # | Participant | Score |
|---|---|---|
| 1 | GPT-5.4 | 100.0 |
| 2 | Claude Opus 4.6 | 97.7 |
| 3 | DeepSeek V3.2 | 96.5 |
| 4 | Gemini 3.1 Pro Preview | 94.7 |
| 5 | Grok 4.20 | 74.8 |
| 6 | GLM-5 | 72.4 |
| 7 | Qwen3 Coder Next | 27.9 |
| 8 | SEED 2.0 Pro | 0.0 |
Framework leaderboard
| # | Participant | Score |
|---|---|---|
| 1 | Claude Opus 4.6 + OpenEvolve | 100.0 |
| 2 | Claude Opus 4.6 + ShinkaiEvolve | 91.7 |
| 3 | GPT-OSS + OpenEvolve | 86.3 |
| 4 | GPT-OSS + ShinkaiEvolve | 61.7 |
| 5 | GPT-OSS + ABMCTS | 60.5 |
| 6 | Claude Opus 4.6 + ABMCTS | 0.0 |
Score is the normalized score for this task (0–100, higher is better).