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tnk-locationallocation's Introduction

Track&Know: Genetic p-Median Solver

Quick Start

If you have your own Open Route Service pass it using the ORS_HOST environment variable:

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 key ibadkureshi/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/

About Track & Know

Track&Know Logo

  • 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

Acknowledgement

"Funded by EU logo" This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 780754.

Background

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.

Maintainers

  • Dr. Ibad Kureshi
  • Dr. Panos Protopapas
  • Ms. Angeliki Mylonaki
  • Mr. Tasos Kakouri

tnk-locationallocation's People

Contributors

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Watchers

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