Supply Chain and Inventory Management – Warehouse Space Optimizer

 

Notes:

• Problem Solved: Optimizes placement of items in a warehouse to minimize retrieval time and maximize space usage.

• Benefits: Improves picking efficiency and reduces labor costs in warehousing operations.

• Adoption: Integrate with WMS (Warehouse Management Systems) for real-time bin allocation.

Python Code:

import pandas as pd

class SpaceOptimizer:

    def __init__(self, item_data):

        self.df = pd.DataFrame(item_data)

    def optimize(self):

        # Sort items by frequency of picking (descending)

        self.df = self.df.sort_values('PickFrequency', ascending=False)

        self.df['AssignedZone'] = ['Front' if i < len(self.df)*0.3 else 'Middle' if i < len(self.df)*0.7 else 'Back'

                                   for i in range(len(self.df))]

        return self.df[['ItemID', 'PickFrequency', 'AssignedZone']]

# Sample item data

items = [

    {'ItemID': 'X1', 'PickFrequency': 120},

    {'ItemID': 'X2', 'PickFrequency': 75},

    {'ItemID': 'X3', 'PickFrequency': 30},

    {'ItemID': 'X4', 'PickFrequency': 10},

    {'ItemID': 'X5', 'PickFrequency': 50},

]

optimizer = SpaceOptimizer(items)

optimized_layout = optimizer.optimize()

print(optimized_layout)