Packing Graphs with ASP for Landscape Simulation
Authors: Thomas Guyet, Yves Moinard, Jacques Nicolas, René Quiniou
IJCAI 2016 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | Experiments were conducted on a database of simulated and real landscapes. and Figure 6 shows that computation time of the procedural approach is comparable with our approach for small graphs (sizes 16 and 21), but increases very quickly with the graph size. Beyond size 26, the procedural approach cannot solve the packing within the timeout period whereas our ASP encoding does. |
| Researcher Affiliation | Academia | 1AGROCAMPUS-OUEST/IRISA UMR 6074, France, 2INRIA Centre Rennes Bretagne Atlantique, France |
| Pseudocode | Yes | Listing 1 introduces an ASP program for the packing problem. |
| Open Source Code | Yes | all programs and instances can be found at https://sites.google.com/site/graphpacking/ |
| Open Datasets | Yes | 7*40 graphs1 of size going from 16 to 61 vertices were randomly generated with a fixed edge density set to 1.2. and Experiments have been done for 4 real landscapes containing up to 200 plots with edge densities of about 3. and footnote 1: all programs and instances can be found at https://sites.google.com/site/graphpacking/. |
| Dataset Splits | No | The paper mentions conducting experiments on simulated and real landscapes but does not provide specific details on how the data was split into training, validation, or testing sets (e.g., percentages, sample counts, or specific predefined splits). |
| Hardware Specification | No | The paper states that experiments were conducted 'on a desktop computer without parallelism', but it does not provide specific hardware details such as CPU/GPU models, memory, or other detailed computer specifications. |
| Software Dependencies | Yes | The ASP solver clingo (version 4.5) [Gebser et al., 2011] was used on a desktop computer without parallelism for a quantitative evaluation of the efficiency of packing programs. |
| Experiment Setup | Yes | 7*40 graphs1 of size going from 16 to 61 vertices were randomly generated with a fixed edge density set to 1.2. and Figure 6 presents the computation times for packing random graphs with 10 structures containing at most 4 edges (5 vertices). |