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IS480 Team wiki: 2010T1 Cowabunga WarehouseOptimization

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Warehouse Optimization

The module answer the most important question: “Where do I put this new product that will maximize and optimize my warehouse”. Based on current business practice and requirements, we have designed a algorithm to measure product’s optimization rate (match by grid-product).

Watch Video: Warehouse Decisions Video

3 key modules: Warehouse & Inventory Utilization Module; Warehouse & Inventory Optimization Module; Warehouse Grid Constraint Module.



Warehouse Grid Constraint Module

Functionality 1: Grid Constraint Management

Each Warehouse Square Grid have 3 parameters that will be used to make the decision on where a product is to be placed.

CowabungaWarehouseGriding.jpg
  1. Volume
    • Height
  2. Accessibility
    • How easy to retrieve from the this location
  3. Sensitivity
    • How cold is this area



As such, each product also has its own parameters which will be used to map and find the most suitable warehouse address for it.

CowabungaCarton.jpg
  1. Carton Dimensions
    • Height
  2. Demand
    • Average Inventory on Hand
  3. Turnover Rate
    • How fast it moves in and go out of the warehouse
  4. Volatility
    • How fast the productʼs quality get compromised (Turn Brown)





Warehouse & Inventory Maximization Module

Functionality 1: Maximization Management

To achieve maximization, our system will first loop through to find addresses that can fit the product's inflow inventory amount. However, in order not to under-utilise the space, we would use Maximization Rate of the Address to set a range to select suitable addresses.

Maximization Rate is calulated as follows:

CowabungaMaximizationRate.jpg

The threshold range would be 50% - 100%. Meaning, if any addresses used to fit the product's inventory amount can only be utilised less than 50%, it would not be considered at all. Similarly, if it exceeds 100%, it would mean that the address is too small to fit all the product's inventory and thus would also not be considered for assignment.



Warehouse & Inventory Optimization Module

Functionality 1: Optimization Management

As mentioned earlier, using the address's paramenters and the product's parameters, we will use algorithms to find a matching address for the products to achieve warehouse optimization.

Our algorithm will calculate the percentage of suitability of the address for the product based on the following parameters:

CowabungaMatchingParameters.jpg

  • Address's Accessibility
  • Address's Sensitivity
  • Product's Turnover Rate
  • Product's Volatility



Optimization Algorithm

Percentage of Suitability
=({1 + [(accessibility – turnoverRate) x 0.20]} x percentage of importance of turnoverRate) + 
 ({1 + [(sensitivity – volatility) x 0.20]} x percentage of importance of volatility)

Based on the calculated percentage of suitability, we will select the address with the minimum difference from 100%.

CowabungaExample1.jpg

Swapping

However, in the case scenario where the percentage of suitability are all below 70%, it means that the address available are all not able to cater to the product's requirements. As such, we carry out one swapping to achieve a higher level of optimization.

Steps Taken:

  1. To find partially occupied/full occupied addresses that will be maximised if allocated to product.
  2. Out of the selected addresses fom step 1, we will find the most suitable one using the percentage of suitability.
  3. If the product occupying the most suitable address is able to fit into another empty address, we will shift it out to the empty and replace the address with the new incoming product. This is SWAPPING.



Reason for swapping

  • Increases optimization rate
    • When you can fully use the conditions that the grids are able to offer, you optimize the warehouse conditions.
  • Brings us one level closer to global optimization.
    • Since we are unable to achieve global optimization due to the warehouse restrictions such as lack of automated arrangement of goods, we can only use heurestic algorithms to cater to all the warehouse operations requirements. With swapping, we are able to be one step closer to achieving global optimization.
  • Efficiency is not compromised
    • Due to first in first out arrangment of goods, the warehouse personnel will always have to shift the goods out first. Therefore, swapping actually shares the same and similar amount of steps required for an incoming batch of goods, therefore efficiency is not compromised.