Convergent Plans for Large-Scale Evacuations
Authors: Caroline Even, Victor Pillac, Pascal Van Hentenryck
AAAI 2015 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | Experimental results on a real case study show that the two-stage approach produces better primal bounds than the MIP model and is two orders of magnitude faster; It also produces dual bounds stronger than the linear relaxation of the MIP model. Finally, simulations of the evacuation demonstrate that convergent evacuation plans outperform existing approaches for realistic driver behaviors. |
| Researcher Affiliation | Academia | 1National ICT Australia (NICTA), Melbourne, Australia 2Australian National University (ANU), Canberra, Australia |
| Pseudocode | Yes | Algorithm 1 The two-stage Algorithm TDFS for the CEPP; Algorithm 2 The two-stage Algorithm TDFS-CT for the CEPP with Minimization of the Clearance Time |
| Open Source Code | No | The paper does not contain any statement about releasing source code or provide a link to a code repository. |
| Open Datasets | No | The paper mentions using data from a 'real case study' of the Hawkesbury-Nepean (HN) floodplain and describes its characteristics (nodes, edges, time horizon, scaled instances) but does not provide a link, DOI, or a citation to a publicly accessible version of this specific dataset. |
| Dataset Splits | No | The paper does not specify explicit training, validation, or test dataset splits. It evaluates on different problem instances (HN80-Ix) but does not detail data partitioning for model training or validation. |
| Hardware Specification | Yes | The algorithms were implemented using JAVA 7 and GUROBI 5.6 and the results were obtained on 64bits machines with 2.8GHz AMD 6Core Opteron 4184 and 32Gb of RAM. |
| Software Dependencies | Yes | The algorithms were implemented using JAVA 7 and GUROBI 5.6 |
| Experiment Setup | Yes | The time horizon H spans 10 hours discretized into 5 minutes time-steps. For each iteration of TDFS, we allocate 30s for each call to TDP. ...the TDP-CT model is stopped after 30s when the duality gap is lower than 1%. |