# The Transportation Model Method: Uses & Examples

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• 0:04 Point A to Point B
• 1:23 The Model
• 3:15 Location Decisions
• 4:11 Lesson Summary
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Lesson Transcript
Instructor: Martin Gibbs

Martin has 16 years experience in Human Resources Information Systems and has a PhD in Information Technology Management. He is an adjunct professor of computer science and computer programming.

Transportation costs can drag down profitability and efficiency in an organization. This lesson describes the use of the transportation model as a means to reduce transit costs.

## Point A to B

The transportation model addresses the concept of moving a thing from one place to another without change. It assumes that any damage en route has negative consequences, and so it's used to analyze transportation systems and find the most efficient route for resource allocation. The model requires only a few data elements:

• Origin of supply
• Destination
• Unit cost of shipping (per-unit cost)

The point is to develop an optimized shipping plan that comes with a minimum of cost; in other words, the path of least resistance. We use the model to determine the minimum cost to ship from several sources to several destinations. Because it is a model, we have to make some assumptions. These assumptions are:

• Items are homogeneous
• Shipping costs per unit are the same, no matter the quantity
• Only one route is chosen between origin and destination

You'll notice in the diagrams to follow that we refer to supply and demand. Supply equals the output a given source can put out (for example, a canning factory producing cans of corn). Demand is the amount the source is asking for (for example, the warehouse in Fargo demands 300 cans, but the factory can only produce 200).

Let's take a look at the model in action.

### The Model

The following table highlights the model in terms of supply and demand between warehouse and factory. Rows A, B, and C show the cost to ship one unit from that factory to Warehouses 1, 2, 3, or 4. The last row and last column each display supply and demand. Let's say each factory is supplying each warehouse with X number of widgets.

Now we need to find the most feasible distribution plan. We will use the intuitive approach, which looks at cost first. Looking at our table, we will start with the lowest cost and reallocate units to that cell. This will repeat until we've allocated all units.

1. Identify the lowest cost cell.
2. Allocate units to that cell, crossing out the row or column that's exhausted.
3. Find cells with the next lowest cost.
4. Repeat steps 2 and 3 until units are allocated.

In our example, the lowest cost is Factory A, Warehouse 4 (\$1). Factory A supplies 150, but demand is 200. We can only supply a maximum of 150 to this cell. Since we satisfied the supply, we can reduce the demand down to what's left: 200 - 150 = 50.

This process is repeated until the cost for shipping from multiple sources results in the lowest cost. We won't go through every iteration, but the final analysis might wind up looking like the following (bold numbers indicate supply):

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