Mizux

#!/usr/bin/env python3
# [START program]
"""Vehicles Routing Problem (VRP) for delivering items from any suppliers.
Description:
Need to deliver some item X and Y at end nodes (at least 11 X and 13 Y).
Several locations provide them and even few provide both.
* fleet
  * vehicles: 2
  * x capacity: 15
  * y capacity: 15

Mizux

#!/usr/bin/env python3
from ortools.constraint_solver import routing_enums_pb2
from ortools.constraint_solver import pywrapcp


def create_data_model():
    """Stores the data for the problem."""
    data = {}
    data['distance_matrix'] = [
        [

Mizux

#!/usr/bin/env python3
"""Example of a simple team scheduling problem."""
from ortools.sat.python import cp_model

def main(n):
    # Data.
    num_teams = 2 * n
    num_rounds = n
    num_games = n
    all_teams = range(num_teams)

Mizux

#!/usr/bin/env bash
# First, disable the workflow you want to delete (via Github console) before executing this script.

# This script need gh cli and jq
# ref: https://github.com/cli/cli
# ref: https://github.com/stedolan/jq
set -euo pipefail

command -v gh
command -v jq

Mizux

#!/usr/bin/env python3
"""Capacitated Vehicle Routing Problem"""
from six.moves import xrange
from ortools.constraint_solver import pywrapcp
from ortools.constraint_solver import routing_enums_pb2
import networkx as nx
import matplotlib.pyplot as plt
import random
import math
import pandas as pd

Mizux

from ortools.constraint_solver import routing_enums_pb2
from ortools.constraint_solver import pywrapcp

# Create Data Model
def create_data_model():
    """Stores the data for the problem."""
    data = {}
    data['time_matrix'] = [
    [0,77,157,140,258,233,289,175,202,479,209,275,641,299,108,83,151,198,246,0,125,319,321,607,408,336,274,502,268,227,461,393,505,445,373,835,725,325,82,27,180,186,388,193,29,29,29,575,23,163,117,672,79],
    [77,0,234,217,221,189,272,144,280,556,286,248,718,376,175,53,154,265,209,77,203,283,277,684,485,413,351,579,345,304,538,376,582,522,440,912,802,402,159,104,257,142,465,270,106,106,106,652,100,126,184,749,82],

Mizux

#!/usr/bin/env python3
#### dial-a-ride problem with time window and maximum riding time

from ortools.constraint_solver import routing_enums_pb2
from ortools.constraint_solver import pywrapcp
#import pandas as pd
import math


# Create Data Model

Mizux

#!/usr/bin/env python3
from ortools.constraint_solver import routing_enums_pb2
from ortools.constraint_solver import pywrapcp

time_mat = [
    [
        0, 998, 940, 336, 4003, 2039, 1786, 791, 651, 1027, 470, 1143, 761,
        1390, 118, 3525
    ],
    [

Mizux

#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""vrp_plot.py
Simple Vehicle Routing Problem with display using plotlib

In the *Vehicle Routing Problem (VRP)*, the goal is to find optimal routes for multiple vehicles visiting a set of locations. (When there's only one vehicle, it reduces to the Traveling Salesman Problem.)
This example of a VRP in which the goal is to minimize the longest single route.

Imagine a company that needs to visit its customers in a city made up of identical rectangular blocks.

Mizux

#!/usr/bin/env python3
#import pandas as pd
from ortools.constraint_solver import pywrapcp

def cvrptw(
        distance_mtx,
        duration_mtx,
        capacities,
        demands,
        loading_times,