Skip to content

mpyrek/MiAPD

Repository files navigation

Choosing the best skiing hotel with the AHP/EVM method 🏂🏼

This is a simple desktop python application for the Decision Algorithms 2022/23 course project.

Short description

The application uses the AHP/EVM method to compare skiing hotels. It allows the user to select their preferences based on few particular features, compares the possible options and finds the most suitable one.

The user can compare the hotels in terms of:

  • price (£)
  • distance from lift (m)
  • altitude (m)
  • total piste distance (km)
  • total lifts
  • total gondolas

Installation & requirements

To run the program the user should:

  • have a Python version: 3.10+ installed

  • install all the packages listed in the requirements.txt file by running the following command in the terminal

    pip install -r requirements.txt

  • run the following command

    python main.py

Libraries used:

  • numPy
  • tkinter
  • pandas
  • csv
  • Azure theme for ttk

Usage

Firstly, the user chooses the criterion which they consider the most important and its target range. Secondly, the application selects 3 most favorable options. Then, the user clicks "Get the Expert's view" and the expert (potentially the user) compares the 3 above-mentioned options - hotels in terms of every criterion using Saaty's 1-9 scale. After that, the user clicks "Get weights" and similarly the expert compares all the criteria with each other. Finally, we can calculate the result after clicking "Calculate".

Here is a simple video of the app in action:

addStat

Method

Hotel selection is based on AHP method described in the book by Konrad Kułakowski's entitled "Understanding the analytic hierachy process."

Tests

To check correctness of the method manual tests have been done.

Capabilities Application development

To develop app we can extend experts' modules and clarify their task. To make the application easier to use, user manuals could be extended.

Authors

Sources

About

No description, website, or topics provided.

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published