WillianFuks

{{
    config(
        materialized='incremental'
    )
}}


with orders as (
  select * from {{ ref('stg__orders') }}
),

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"""
Encrypts or Decrypts messages. For encryption:

    python cipherize.py --message=test --action=encrypt

    or

    python3 cipherize.py --filepath /path/to/file --action encrypt

Decryption:

WillianFuks

@pytest.mark.django_db
def test_data_2():
    """
    Force overbooking of ships.
    """
    name = 'test2'
    f = Files.objects.create(name=name)
    f.save()

    demand_data = [

WillianFuks

def optimize(data_models, train_limit, ob_cost_factor=2, container_cost_factor=10):
    results = {}
    containers = data_models['containers']
    shippers = data_models['shippers']
    orig_ports = data_models['orig_port']
    transp = data_models['transp']
    transp_train_map = data_models['transp_train_map']
    shipper_trade_spaces = data_models['shipper_trade_spaces']
    overbooking_spaces = shipper_trade_spaces.matrix
    dest_shipper_map = data_models['dest_shipper_map']

WillianFuks

import numpy as np
import cvxpy as cx

# Begin with variables
x_shippers = cx.Variable((4, 2), boolean=True, name='shippers')
x_transports = cx.Variable((4, 2), boolean=True, name='transports')
x_docks = cx.Variable((4, 2), boolean=True, name='docks')

# 'y' represents variables that are built by introducing an AND conjunction between
# 2 other variables.

WillianFuks

import numpy as np
import cvxpy as cx


# Begin with the variables that describe the problem
x_shippers = cx.Variable((4, 2), boolean=True, name='shippers')
x_transports = cx.Variable((4, 2), boolean=True, name='transports')

# Data that helps implement the model
containers = np.array([[200, 0], [300, 1], [400, 0], [500, 1]])

WillianFuks

import numpy as np
import cvxpy as cx

# First the data that sets the problem
container_costs = np.array([200, 300, 400, 500])
shippers_costs = np.array([100, 130])
shippers_spaces = np.array([2, 1])

# Main variable to be optimized
x_shippers = cx.Variable((4, 2), boolean=True, name='shippers')

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