InventoryOptimization
Task 11 / 47
finite_horizon_dp
Finite-horizon stochastic inventory control via time-varying policies minimizing discounted or total expected cost over a known horizon. State may include on-hand inventory and information delays; scoring rolls out costs and constraint violations—typical for promotional or seasonal planning.
Model leaderboard
| # | Participant | Score |
|---|---|---|
| 1 | GPT-5.4 | 100.0 |
| 2 | Claude Opus 4.6 | 99.8 |
| 3 | Grok 4.20 | 79.6 |
| 4 | DeepSeek V3.2 | 69.5 |
| 5 | GLM-5 | 68.4 |
| 6 | Gemini 3.1 Pro Preview | 60.6 |
| 7 | SEED 2.0 Pro | 56.0 |
| 8 | Qwen3 Coder Next | 0.0 |
Framework leaderboard
| # | Participant | Score |
|---|---|---|
| 1 | Claude Opus 4.6 + OpenEvolve | 100.0 |
| 2 | Claude Opus 4.6 + ShinkaiEvolve | 62.5 |
| 3 | GPT-OSS + ShinkaiEvolve | 36.6 |
| 4 | Claude Opus 4.6 + ABMCTS | 14.8 |
| 5 | GPT-OSS + OpenEvolve | 4.0 |
| 6 | GPT-OSS + ABMCTS | 0.0 |
Score is the normalized score for this task (0–100, higher is better).