data.py

max_volume = {
    1: 15 * 0.4 + 15 * 0.8, 
    2: 15 * 0.4 + 15 * 0.8, 
    3: 20 * 0.4 + 20 * 0.8, 
    4: 20 * 0.4 + 20 * 0.8, 
    5: 15 * 0.4 + 15 * 0.8, 
    6: 20 * 0.4 + 20 * 0.8, 
    7: 30 * 0.4 + 30 * 0.8, 
    8: 30 * 0.4 + 30 * 0.8, 
    9: 35 * 0.4 + 35 * 0.8, 
    10: 25 * 0.4 + 25 * 0.8, 
    11: 30 * 0.4 + 30 * 0.8, 
    12: 30 * 0.4 + 30 * 0.8, 
    13: 30 * 0.4 + 30 * 0.8, 
    14: 35 * 0.4 + 35 * 0.8, 
    15: 30 * 0.4 + 30 * 0.8, 
    16: 40 * 0.4 + 40 * 0.8, 
    17: 25 * 0.4 + 25 * 0.8, 
    18: 20 * 0.4 + 20 * 0.8, 
    19: 15 * 0.4 + 15 * 0.8, 
    20: 20 * 0.4 + 20 * 0.8, 
}

# location
# origin (0, 0) is top left corner of the rectangular outline of size (12 x 6) 
shop_location = {
    1: (2, 0), 
    2: (10, 0), 
    3: (3, 1),
    4: (5, 1),
    5: (8, 1),
    6: (0, 2),
    7: (2, 3),
    8: (6, 3),
    9: (10, 3),
    10: (12, 3),
    11: (1, 4),
    12: (4, 4),
    13: (11, 4),
    14: (3, 5),
    15: (8, 5),
    16: (10, 5),
    17: (2, 6),
    18: (4, 6),
    19: (7, 6),
    20: (12, 6)
}


warehouse_location = [(4, 3), (9, 4)]

###############################

def get_warehouse_to_shop_distance():
    # calculate rectilinear distance | x1 - x2 | + | y1 - y2 |
    dij = [
        [], []
    ]

    for i, warehouse in enumerate(warehouse_location):
        for shop in shop_location.values():
            dij[i].append(abs(warehouse[0] - shop[0]) + abs(warehouse[1] - shop[1]))

    return dij

dij = get_warehouse_to_shop_distance()


bip = [
    [650, 650],
    [650, 650]
]


ajp = [[[1, 6], [1, 5], [2, 6], [2, 8], [2, 5], [2, 8], [3, 13], [3, 9], [5, 12], [3, 9], [3, 10], [4, 12], [4, 13], [4, 12], [3, 11], [6, 12], [4, 10], [2, 7], [1, 6], [2, 7]],
 [[3, 3], [3, 4], [5, 4], [4, 5], [4, 4], [6, 4], [7, 5], [6, 7], [8, 6], [6, 7], [8, 7], [6, 4], [7, 7], [7, 8], [6, 7], [11, 9], [6, 5], [4, 4], [4, 3], [4, 4]], [[4, 1], [4, 2], [6, 3], [7, 3], [6, 2], [5, 2], [11, 4], [9, 4], [12, 5], [6, 3], [9, 3], [10, 4], [10, 4], [9, 5], [9, 5], [14, 5], [8, 3], [7, 2], [6, 2], [8, 2]], [[7, 1], [6, 1], [9, 1], [7, 1], [5, 1], [7, 1], [12, 2], [13, 2], [15, 2], [10, 1], [12, 2], [10, 2], [11, 1], [15, 2], [12, 2], [18, 2], [11, 1], [10, 1], [5, 1], [9, 1]], [[7, 0], [8, 0], [9, 0], [10, 0], [8, 0], [7, 0], [12, 0], [21, 0], [18, 0], [14, 0], [12, 0], [16, 0], [14, 0], [15, 0], [14, 0], [18, 0], [9, 0], [8, 0], [7, 0], [10, 0]], [[6, 0], [5, 0], [8, 0], [9, 0], [6, 0], [9, 0], [11, 0], [14, 0], [18, 0], [11, 0], [15, 0], [14, 0], [16, 0], [15, 0], [17, 0], [17, 0], [13, 0], [9, 0], [7, 0], [8, 0]], [[7, 0], [6, 0], [9, 0], [8, 0], [7, 0], [12, 0], [12, 0], [14, 0], [17, 0], [12, 0], [15, 0], [14, 0], [14, 0], [18, 0], [13, 0], [19, 0], [12, 0], [9, 0], [5, 0], [9, 0]], [[7, 1], [7, 1], [8, 1], [7, 1], [8, 1], [9, 1], [12, 1], [13, 2], [11, 2], [9, 1], [13, 2], [15, 2], [10, 2], [11, 2], [13, 1], [19, 2], [11, 1], [8, 1], [5, 0], [9, 1]], [[5, 1], [4, 2], [7, 2], [6, 2], [4, 2], [7, 3], [11, 3], [11, 3], [12, 4], [10, 3], [10, 4], [10, 4], [10, 4], [10, 4], [11, 4], [14, 6], [7, 2], [6, 2], [4, 2], [8, 2]], [[4, 3], [4, 3], [5, 5], [5, 3], [3, 4], [5, 4], [8, 6], [7, 7], [6, 8], [5, 6], [6, 6], [6, 7], [8, 7], [9, 8], [8, 7], [8, 8], [6, 4], [4, 4], [3, 3], [5, 4]], [[1, 4], [1, 5], [2, 7], [2, 7], [2, 5], [2, 7], [3, 9], [4, 11], [4, 10], [3, 8], [3, 11], [3, 11], [3, 8], [4, 15], [4, 11], [5, 14], [3, 9], [2, 8], [1, 6], [1, 6]], [[0, 6], [0, 8], [0, 10], [0, 10], [0, 7], [0, 10], [0, 13], [0, 15], [0, 14], [0, 12], [0, 12], [0, 13], [0, 14], [0, 18], [0, 15], [0, 20], [0, 13], [0, 7], [0, 7], [0, 10]]]