# Net palette weight and optimization

```
import numpy as np
# Some typical pallet sizes in the EU (Source: Wikipedia, "Pallet")
# width (mm), length (mm), height (mm), pallet weight (kg), max load (kg)
pallets_eu = """
800,1200,145,22.5,2490
1200,1200,144,33,1470
1000,1200,144,29,1920
800,600,144,9.5,500
"""
rows = pallets_eu.split('\n')[1:-1]
data = np.array([list(map(float, row.split(','))) for row in rows])
vol_m3 = (data[:,0] * data[:,1] * data[:,2]) / 10**9
max_load = data[:,-1]
density = data[:,-2] / vol_m3
metric = max_load / density
print(list(map(lambda x: float("%.2f" % x), metric)))
# [15.4, 9.24, 11.44, 3.64]
# The first pallet type has the most beneficial characteristics.
# Given the first pallet type, how many pallets would fit in a truck with known dimensions and how much would their total weight be (fill weight without goods)? Assume that 3 stacked pallets approximate the truck height.
truck_length_m = 13.6
truck_height_m = 2.45
truck_width_m = 2.45
pallets_in_length = truck_length_m // (data[0,1] / 1000)
pallets_in_width = truck_width_m // (data[0,0] / 1000)
pallets_in_height = 3
total_pallets = pallets_in_length * pallets_in_width * pallets_in_height
total_pallets_weight_kg = total_pallets * data[0, -2]
print(total_pallets, total_pallets_weight_kg) # 99, 2227.5
# A 13.6m-long truck would carry 99 pallets weighting 2227.5kg per trip.
# Could pallet weight optimization reduce freight cost and emissions?
# Idea: Collected plastics could be used to produce lightweight plastic pallets.
# According to Wikipedia, these weigh 1.4 - 6.8kg or 14kg.
```