运筹优化模型分解对比框架 | Operations Research Decomposition Benchmarking Framework
标准化拆分集成模型为子问题流水线,公平对比求解性能 | Standardized pipeline for splitting integrated OR models into subproblems with fair performance comparison
运筹优化模型分解对比框架:标准化拆分集成模型为子问题流水线,公平对比求解性能。
Operations Research decomposition benchmarking framework: standardized pipeline for splitting integrated OR models into subproblems with fair performance comparison.
- 模块化拆分 | Modular Decomposition:按决策域/时间/空间/资源维度拆解模型 | Split by decision domain/time/space/resource
- 标准流水线 | Standard Pipelines:集成基线、顺序求解、迭代修复、主从分解 | Integrated baseline, sequential, iterative, master-sub
- 公平对比 | Fair Comparison:统一实例、预算、随机种子 | Unified instances, budgets, random seeds
- 可复现 | Reproducible:结构化输出与配置管理 | Structured outputs and configuration management
识别决策变量、耦合约束、目标组成 | Identify decision variables, coupling constraints, objective components
- 必选 | Required:集成基线 | Integrated baseline
- 可选 | Optional:顺序/迭代/主从分解(选 1-3 条)| Sequential/iterative/master-sub (choose 1-3)
# 配置流水线 | Configure pipelines
pipelines:
- Integrated_Baseline
- Sequential_A_B
# 运行 | Execute
python run_benchmark.py --config config.yaml
# 输出 | Outputs
results/{instance}/{pipeline}/summary.jsonpython aggregate_results.py --output report.csv{
"instance": "case01",
"pipeline": "Sequential_A_B",
"solver": {"status": "optimal", "wall": 120.5, "gap": 0.005},
"objective": {"total": 1050.2, "components": {...}},
"coupling": {...}
}Decomp4OR/
├── config.yaml # 流水线配置 | Pipeline configuration
├── models/ # 模型实现 | Model implementations
│ ├── integrated.py
│ └── decomposed.py
├── pipelines/ # 流水线定义 | Pipeline definitions
├── instances/ # 实例数据 | Instance data
├── results/ # 求解结果 | Solving results
└── scripts/ # 执行脚本 | Execution scripts
详见 SPEC.md 完整规范 | See SPEC.md for full specification
MIT