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A rideshare planner that gives an optimal plan for multiple drivers and passengers using Z3 Solver

Project description

Z3 Rideshare Planner

Introduction

This Python package provides a planner that takes in the names and addresses of multiple passengers and drivers, and the address of a destination, and gives a plan which minimizes the time for pickup process.

This package utilizes [[https://www.microsoft.com/en-us/research/project/z3-3/|Microsoft Z3 Solver]] and [[https://developers.google.com/maps|Google Map API]].

Google Map API Key

To use this package, you need to have a Google Map API Key. You can get one for free at https://console.cloud.google.com/google/maps-apis/credentials.

Dependencies

  • googlemaps
  • matplotlib
  • datetime
  • folium
  • z3-solver
  • polyline
  • numpy

Usage

Class: Planner

  • Planner.__init__(self, API_KEY) Takes in a Google API Key, returns a Planner instance.

  • Planner.configure(self, passenger_name_addr, driver_name_addr, destination, n_seats, must_together=[]) Takes in requirements and conditions.

    • passenger_name_addr: List of 2-tuples, where the first element is the passenger name, and the second element is their address
    • driver_name_addr: List of 2-tuples, where the first element is the driver name, and the second element is their address
    • destination: The final destination that everyone goes to
    • n_seats: Specifies the capacity (driver included) of each car. If the input is an int, then it's for all drivers; If the input is a list of int, then the list elements each represents the capacity of one car, according to the order of ``driver_name_addr```
    • must_together: List of lists, where each element list contains a group of passengers and (at most one) driver that must be in the same car
  • Planner.solve(self) If a plan is found, prints "Plan found!". Otherwise, raises ValueError.

  • Planner.print_plan(self) If a plan has been found, print the plan in the string format.

  • visualize(self, output_mode='html', relative_path=None, colormap='Set1') If a plan has been found, visualize it with interactive features.

    • output_mode: If output_mode='html', save the visualization as an html file at relative_path; If output_mode='display', returns a folium.Figure object
    • colormap: A str key of matplotlib.colormaps, serves as the color scheme of the markers on the map

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