Getting Started With Intelligent Greenfield Analysis

Greenfield Analysis Overview

Greenfield analysis (GF) is a method for determining the optimal location of facilities in a supply chain network. ​The Greenfield engine in Cosmic Frog is called Triad and this name comes from the oldest known species of frogs – Triadobatrachus. You can think of it as the starting point for the evolution of all frogs, and it serves as a great starting point for modeling projects too! We can use Triad to identify 3 key parameters: ​

1. The optimal number of distributions centers ​
2. The location of each distribution center​
3. Which customers should be served by which distribution center​

GF is a great starting point for network design—it solves quickly and can reduce the number of candidate site locations in complicated design problems. However, a standard GF requires some assumptions to solve (e.g. single time period, single product). As a result, the output of a Triad model is best suited as initial information for building a more robust Cosmic Frog optimization (Neo) or simulation (Throg) model.​

Running Your First Greenfield Analysis​

You can run GF in any Cosmic Frog model. Running a GF model only requires two input tables to be populated: ​

1. Customers​
2. Customer Demand

1. We are in the Data module of Cosmic Frog, which can be selected from the Module menu (icon with 3 horizontal bars).
2. The technology filter has been used to only show GF (Triad) tables and fields in the user interface, simplifying it considerably.
3. By clicking on the square grid icon input tables are shown. Switching to the output and custom tables can be done by clicking on the round grid icon and grid with solid top rows icons, respectively.
4. The 2 required input tables for GF, Customers and Customer Demand, can be found in the Model Elements and Demand sections of the Input Tables list.

A third important table for running GF is the Greenfield Settings table in the Functional Tables section of the input tables. We call our GF approach “Intelligent Greenfield” because of the different parameters available by configuring this settings table.​ The Greenfield Settings table is always populated with defaults and users can change these as needed. See the Greenfield Setting Explained help article for an explanation of the fields in this table.

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A greenfield analysis starts with clicking the “Run” button at the right top of the Cosmic Frog application, just like a Neo or Throg model.​​

After clicking on the Run button, the Run screen comes up:

1. We are in the Run screen.
2. In the Engine section, select “Triad (Intelligent Greenfield)” as the engine to use.
3. The scenario(s) to be run with the Triad engine can be selected here. Multiple scenarios with different inputs in the Customers and Customer Demand input tables and different settings in the Greenfield Settings table can be run simultaneously.
4. When ready to run the GF scenarios, click on the Run button or click on the Cancel button to close the window without kicking off any runs.​

Greenfield Scenarios

Besides making changes to values in the Customers and/or Customer Demand tables, GF scenarios often make changes to 1 or multiple settings on the Greenfield Settings table. The next screenshot shows an example of this:

1. From the Module menu we have chosen Scenarios to go the Scenarios part of Cosmic Frog.
2. In the list of scenarios set up in the model, there is one named 01b_7 Optimal Facilities.
3. This scenario has 4 scenario items of which the second one, named Max 7 New Facilities, is selected and this is the one of which the configuration is shown on the right hand-side.
4. The Greenfield Settings table is selected as the table to which the scenario item’s changes apply.
5. The action is set to change the value of the Max Number Of New Facilities field in the Greenfield Settings table to 7.

Customer Clustering

To improve the solve speed of a Triad model, we can use customer clustering. Customer clustering reduces the size of the supply chain by grouping customers within a given geometric range into a single customer.​ We can set the clustering radius (in miles) ​in the Greenfield Settings table in the Customer Cluster Radius column.​​

Clustering is optional, and leaving this column blank is the same as turning off clustering.

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While grouping customers can significantly improve the run time of the model, clustering may result in a loss of optimality. However, Greenfield is typically used as a starting point for a future Neo optimization model, so small losses in optimality at this phase are typically manageable.