If you have your own Open Route Service pass it using the ORS_HOST environment variable:
docker run -p 8000:8000 -e ORS_HOST=
*https://yourhost/ors*` ibadkureshi/tnk-pmed:latest`
If you are using the public Open Route Service (the API playground) pass you key to the code
docker run -p 8000:8000 -e ORS_KEY=
your keyibadkureshi/tnk-pmed:latest
# this is not recommended due to rate limits and the code doesnt optimise against number of api/routing calls
Then open a browser and go to http://localhost:8000/
- Project Title - Big Data for Mobility Tracking Knowledge Extraction in Urban Areas
- Project Website - https://trackandknowproject.eu/
- Work Package - WP4: Big Data Analytics (BDA Toolbox) [Leader: CNR]
- Task & Deliverable - 4.1 Analytics for mobility patterns detection and forecasting [Leader: UPRC]
- Component Leader - Inlecom Group
This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 780754.
Location-allocation problems typical deal with provisioning of resources between facilities based on historic demand. The p-median approach is one such model that aims to minimise the total demand-weighted distance between the demand points and the facilities. This NP-Hard problem aims to locate p facilities to serve n demand, by minimising the total demand-weighted distance between the facilities and the demand.
The Track&Know Genetic p-Median Solver uses a genetic algorithm approach to solve the problem in polynomial time. This tool plays an important role in translating mobility information into policy and management recommendations. This project in a parallelised and containerised implementation in python of a Genetic Algorithm approach to solve the p-Median problem. The underlying model is based on the following research paper:
Alp, O., Erkut, E., & Drezner, Z. (2003). An efficient genetic algorithm for the p-median problem. Annals of Operations research, 122(1-4), 21-42.
- Dr. Ibad Kureshi
- Dr. Panos Protopapas
- Ms. Angeliki Mylonaki
- Mr. Tasos Kakouri