Placement of Loading Stations for Electric Vehicles: No Detours Necessary!
Authors: Stefan Funke, Andre Nusser, Sabine Storandt
AAAI 2014 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | Our proposed techniques for computing ESC solutions were evaluated in a multi-threaded implementation written in C++ and executed on 2nd generation intel core desktop hardware, an i7-3930 (6 cores 64GB of RAM) for complete set generations and an i7-2700 (4 cores, 32GB RAM) for the multi-stage construction with nested Hitting Sets. We use the following abbreviations to state results: K=103, M=106, s=seconds, m=minutes, h=hours, d=days, GB=109Bytes. Several road networks of Germany derived from Open-Street Map data (OSM ) were used for evaluation, see Table 1 for an overview. |
| Researcher Affiliation | Academia | Stefan Funke and Andr e Nusser Universit at Stuttgart Institut f ur Formale Methoden der Informatik 70569 Stuttgart, Germany {funke,nusser}@fmi.uni-stuttgart.de Sabine Storandt Albert-Ludwigs-Universit at Freiburg Institut f ur Informatik 79110 Freiburg, Germany storandt@cs.uni-freiburg.de |
| Pseudocode | No | The paper describes algorithms in text, but does not include structured pseudocode or algorithm blocks. |
| Open Source Code | No | The paper does not provide concrete access to source code for the methodology described. |
| Open Datasets | Yes | Several road networks of Germany derived from Open-Street Map data (OSM ) were used for evaluation, see Table 1 for an overview. Energy consumption of an EV was modeled as explained in the introduction using distance data from OSM and elevations provided by the Shuttle Radar Topography Mission (SRT ). The Open Street Map Project http://www.openstreetmap.org. Shuttle Radar Topography Mission http://www2.jpl.nasa.gov/srtm. |
| Dataset Splits | No | The paper uses entire road networks as test instances (e.g., Pforzheim, Tübingen, Germany) and does not describe any training, validation, or test dataset splits in the context of model training or evaluation. |
| Hardware Specification | Yes | Our proposed techniques for computing ESC solutions were evaluated in a multi-threaded implementation written in C++ and executed on 2nd generation intel core desktop hardware, an i7-3930 (6 cores 64GB of RAM) for complete set generations and an i7-2700 (4 cores, 32GB RAM) for the multi-stage construction with nested Hitting Sets. |
| Software Dependencies | No | The paper states 'multi-threaded implementation written in C++', but does not provide specific version numbers for libraries or other software dependencies. |
| Experiment Setup | Yes | Energy consumption of an EV was modeled as explained in the introduction using distance data from OSM and elevations provided by the Shuttle Radar Topography Mission (SRT ). B corresponds to a battery capacity which translates to a certain cruising range (terrain dependent); our α equals 4. For the BW network we computed a k = 32-Hop Cover C (146, 494 nodes) which corresponds to an ESC solution with B = 8832 (and cruising range of about 9km in flat terrain). The bound B is chosen between almost zero and 60 percent of the maximum energy consumption of some shortest path in the respective network. |