Skip to content

Latest commit

 

History

History
51 lines (40 loc) · 2.86 KB

readme.md

File metadata and controls

51 lines (40 loc) · 2.86 KB
Raw

[SHARP] Metaheuristic Optimization - P Median Problem

GitHub license GitHub stars GitHub forks

This repository contains the Jupyter notebooks, text files, and supporting documentation for the project activity on the p-median location problem. The objective of this project is to determine the optimal selection of facilities from a set of potential locations, minimizing the total distance for serving all demand points while ensuring that each demand point is assigned to its nearest selected facility.

Contents

  • Ipyb Files: Contains Jupyter notebooks.

    • Random Sampling - Instance 1.ipynb: Implementing the random sampling algorithm for instance 1.
    • Random Sampling - Instance 2.ipynb: Implementing the random sampling algorithm for instance 2.
    • Local Search - Instance 1.ipynb: Implementing the local search algorithm for instance 1.
    • Local Search - Instance 2.ipynb: Implementing the local search algorithm for instance 2.

  • Text Files: Supplementary text files corresponding to the Jupyter notebooks.

    • Random Sampling - Instance 1.txt: Text file for implementing of random sampling algorithm
    • Random Sampling - Instance 2.txt: Text file for implementing of random sampling algorithm
    • Local Search - Instance 1.ipynb: Text file for implementing of local search algorithm
    • Local Search - Instance 2.ipynb: Text file for implementing of local search algorithm

  • requirements.txt: List of Python packages required to run the notebooks.

  • SHARP_MHO_1.pdf: A comprehensive report detailing solution encoding representation, search procedure explanation, and results obtained for each exercise.

Problem Overview

Given a set of n locations representing demand points and a set of m potential facility locations, the p-median problem aims to determine the optimal selection of p facilities from the set of potential locations.

Instances

  • Instance 1: 100 locations, requiring 15 facilities to be open.
  • Instance 2: 1000 locations, requiring 30 facilities to be open.

Setup & Execution

Setup & Execution

  1. Ensure you have Jupyter Notebook and required Python packages installed.
  2. Clone the repository:
git clone https://github.com/<your_username>/P-Median-Problem.git
  1. Navigate to the cloned directory.
  2. Install required packages:
pip install -r requirements.txt
  1. Run Jupyter Notebook:
jupyter notebook
  1. Open each notebook and execute the cells sequentially.