Using AI (Artificial Intelligence) and ML (Machine Learning) to generate the optimal pallet racking configuration with the least number of bays.
User to input the profile of inventory to be stored. Example, the length, width, height and quantity of the pallets or cartons to be stored.
Next, user to input the physical attributes of the warehouse. Example are the clear height of the warehouse and bay width.
User will then select the mode of analysis, and to set the time limitation of the calculation if required.
The AI (Artificial Intelligence) will utilize various algorithms to analyze the inventory to be stored, and the physical attributes of the warehouse.
This includes Smart Greedy algorithm, Simulated Annealing algorithm, Genetic algorithm and Monte Carlo algorithm.
In parallel, the analysis will also uses historical dataset as seed generations for the algorithms. This is part of the Machine Learning aspect.
The AI script will determine the optimal pallet racking configuration, with the least number of pallet racking bays.
A pictorial representation of the racking bay will also be generated.
User to input the results into the excel, and at the same time, generate the cross section of the pallet racking bay.