1. Intelligent Supply Chain Management Course Transportation Scheduling
i2 U
Intelligent Supply Chain Management Course
Module Thirteen:
Transportation Scheduling

2. Supply Chain Management Key Processes
Fully Integrated top-down directions
Fully Integrated bottom-up feed back _ +
Strategic Supply Chain Planning
Sales & Operations Planning
Number of decisions
Specificities by industries
Impact of decisions
Length of Planning horizon
Master Supply Planning
Inventory Planning
Demand Planning
Production
Distribution
Procurement
Transportation
This module will address the transportation scheduling process, which deals with the management of short-term transportation activities.
Supplier Scheduling
Production Scheduling
Transportation Scheduling
Inventory Deployment
Demand Fulfillment _ +
Reaction to changing supply conditions
Supply Chain Execution Monitoring

3. After Completing This Module, You are Expected to:
Define the key objectives of the Transportation Scheduling process
Understand the typical limitations of the Transportation Scheduling process
Understand the optimization logic embedded in solvers used to optimize the Transportation Scheduling process
Understand the “Dynamic Merge in Transit” process and its criticality to support eBusiness activities
Identify Transportation Scheduling key enablers and their resulting business value
Identify Transportation Scheduling excellence criteria

4. Transportation Scheduling Process Positioning
operational
tactical
strategic
scheduling
buy
make
move
store
sell
demand
fulfillment
This process is actually focused on the very short-term, typically the next day or the next two or three days at maximum.
hours
days
weeks
months
year +

5. Transportation Scheduling Objectives
Substitute estimated transportation lead times with ‘up-to-the-minute’ lead times for a fully valid transportation plan
Minimize transportation costs by building optimal loads and selecting adequate transportation means
Transmission of detailed transportation plans to carriers
There are three objectives supported by the Transportation Scheduling process.
The first objective is to generate a fully valid transportation schedule by substituting all the estimated transportation lead times -- that have been used at the tactical planning levels -- with actual up-to-the-minute lead times.
The second objective is to minimize the transportation costs by building optimal loads, selecting adequate transportation means, and reducing the total mileage by developing optimized routings. In other words, the focus is on trying to prevent the trucks from leaving half empty and coming back totally empty, and also to prevent trucks -- or other transportation modes -- from running around like “headless chickens” because of an irrational routing logic. It is important to mention that this cost minimization is by no means achieved at the expense of negative impact on inventory turns or customer service. The flexibility of the transportation scheduling process is in fact limited in the sense that it is not authorized to modify a production plan or to generate late deliveries. The only authorized change on the supply plan is simply the possibility - if the customer accepts it - to ship some orders earlier than the agreed delivery date in order to broaden the optimization possibilities.
Finally, the third objective is to make sure that there is proper communication and collaboration with the transportation partners that will move the products from one location to another.

6. Typical Limitations in Transportation Scheduling
CUSTOMERS
VMI
CUSTOMER
Empirical “optimization”
DCs
Fragmented transportation scheduling
Incoming goods purchased CIF - no search of combination with internal and outbound transportation
PLANT
The optimization of the transportation scheduling process can be seen as low hanging fruit in many companies, because the management of transportation activities is generally organized by sub-segments of the supply chain network, leading to a fragmented transportation scheduling process.
Also, in many cases, the transportation cost "optimization" is supported by very empirical processes. Besides, most companies are currently not managing the inbound transportation activities, leaving this task to their suppliers (in other words the incoming goods are mostly purchased on a CIF condition) and there is therefore no effective search for combining inbound components with internal and outbound transportation.
SUPPLIERS

7. Transportation Scheduling Optimization
CUSTOMERS
VMI
CUSTOMER
Considering…
Carrier selection
Mode selection
Hub selection
Routing
Backhauling
Deadheads
Minimization of total transportation cost by increasing transportation space utilization and reducing total mileage
DCs
PLANT
The optimization of transportation scheduling requires a global perspective on all the transportation needs of a global supply chain network. To do so, all transportation requirements must be stored in a single data repository. This data then needs to be fed to a solver that will apply a specific optimization logic (which contains a blend of linear and nonlinear programming logics) to minimize the total transportation cost by doing two things:
Increasing the utilization of the transportation space -- in other words, trying to fill the transportation loads as close as possible to 100%.
Reducing the total mileage.
The optimization logic to reach this cost minimization is actually quite complex. It needs to consider variables such as carrier selection, mode selection (when there are alternatives between plane, train, boat or road, etc.), hub selection (i.e., defining where the products should be ideally cross-docked to minimize the transportation costs), routing definition (for minimizing the total transportation mileage), and use of techniques such as backhauling or deadheads (which try to combine different shipments and different routes to minimize the distance during which the trucks or the trains remain empty).
SUPPLIERS

8. Strategies Total cost % red. Total mileage Duration
Typical set of strategies that a solver uses to minimize transportation costs
This rather unattractive slide is not the graphical user interface that will be viewed by the transportation scheduler, but rather a display of the logic used by a transportation scheduling optimization solver, which helps convey how the system works.
On the left hand side of the screen is the list of the strategies that are executed during the solve in order to try to minimize the transportation cost. Some of these strategies have names that are self explanatory like ‘try ship direct’, ‘break truck loads’, ‘delete last leg’, ‘optimize same pick move’, etc.
On the “total cost” column you can see the total cost going down from an initial USD148K - the original cost shown at the bottom of the screen -- to USD103K at the end of the last strategy, which represents only 69% of the original cost.
On the right hand side of the screen you can also see two additional pieces of information: one is the total mileage (which is being reduced further and further by the different strategies), and the duration of each strategy execution and the cumulated duration for the total solver runtime (shown by the last two columns on the right).

9. Output of a Transportation Scheduling Solver: Consolidated Loads
Loads generated by the solve
Detailed shipments by loads
The actual graphical user interface looks like this. It is possible to visualize the loads generated by the solver and to look at the detailed shipments that compose a specific load.

10. Output of a Transportation Scheduling Solver: Graphical Visualization of Selected Lanes
Another useful output is the graphical visualization of the lanes that have been selected by the solver to move the products throughout the whole supply chain network.

11. Load Physical Configuration for Maximum Transportation Space Utilization
Trucks and Trains
Pallets
Cases
In addition to the global optimization capabilities that we just described, a load configuration solver can help further reduce the transportation costs by further maximizing the transportation space utilization.
Such a load configuration solver looks into the physical characteristics of the products being shipped -- width, height, depth, weight, etc. -- to see how these individual products can be optimally combined into cases, how these cases can be optimally combined into pallets, and how these pallets can be optimally located in a container (either a truck or a train), to avoid damage (for instance, not placing steel products on top of eggs…), and also to align the unloading with the delivery routing.
Product

12. Transportation Scheduling: Key Enablers and Related Business Benefits
Global and accurate consideration of transportation needs
Blend of LP / MILP solvers
Full integration with other Supply Chain Management processes
Transportation costs
In summary, the key enablers for transportation scheduling optimization are:
Use of a single data repository containing all data required for full transportation scheduling optimization.
Application of a sophisticated algorithm capable of minimizing the transportation costs by running a combination of optimization strategies supported by linear and nonlinear programming logic.
Integration of these optimization solvers with the other Supply Chain Management processes.
The resulting business benefit is exclusively a reduction in transportation costs, but this reduction can be very significant. By applying solvers, some companies have managed to reduce more than 20% of their transportation costs in a very short period of time.

13. Business Environments Where Detailed Transportation Scheduling is Critical
High volumes
Small shipment sizes
Use of 3rd party carriers
As well-suited for management by manufacturers (shippers) as it is by Third Party Logistics (3PL) providers
The magnitude of the benefits related to the optimization of the transportation scheduling process actually varies significantly depending on the characteristics of the supply chain environment. Characteristics that increase the criticality of transportation scheduling are:
Handling high volumes.
Having small shipment sizes; the smaller the shipment size the higher the potential of optimization because the combinatorial possibilities will be greater.
Using third party carriers: whenever a company uses third party carriers the benefits will be higher because all the transportation costs are purely variable.
It is also important to mention that optimizing the transportation scheduling process can be equally beneficial regardless of whether the process is managed by the shipper (manufacturing or distribution company) or a third party logistics provider.

14. An Increasingly Critical Capability in the e-Business World: Dynamic Merge in Transit
Consolidation of incoming flows at a location dynamically selected to minimize transportation costs
Unique delivery to the customer 5 4
PC manufacturer
The order is automatically dispatched to all supply sources 2
Suppliers provide their promises back 3
Company web server
Printer manufacturer (same company, other division)
A specific capability related to the transportation scheduling process is becoming increasingly critical to survival in the e-business world. This capability, known as "dynamic merge-in-transit", is structured around five steps which are described through the following example:
A customer is making a purchase through the web and decides to buy from a PC company the following: (1) a PC, (2) a printer and (3) some office furniture. What the customer doesn’t know (and actually doesn’t want to know and does not care), is that he just bought three items provided by three different supply locations belonging to two different companies. The customer is also asking to receive a single delivery of all these items.
As soon as the order has been submitted and approved through automatic credit checks, the order fulfillment server automatically dispatches this multiple line order to all the supply sources that will need to fulfill those different items.
Then the suppliers confirm these orders by sending their promises back to the order fulfillment server.
Then the tricky question is where these three incoming product flows should be optimally "merged in transit" in order to ensure a single delivery to the customer.The answer to this question will be dependant on the pattern of the transportation needs during this particular period. Therefore, the choice of a specific distribution center to consolidate all these goods is not a static one. As a result, an optimization logic has to be incorporated into the order fulfillment server. When the distribution center has been selected, the three suppliers will receive the notification on where to ship the products – the location that has been identified for being the most cost effective.
Finally, the process ends up with a single delivery to the customer.
With the dis-intermediation generated by the web economy (i.e., the customer sees fewer sellers in the course of making the a purchase of a group of products), this dynamic merge-in-transit capability is going to become a critical capability. This obviously will require specific technological enablers that most companies do not have today. 1
Customer
A customer orders through the PC company web storefront several products supplied from different locations and actually different suppliers (cross selling)
Office furniture manufacturer (ext supplier)

15. Transportation Scheduling Process Excellence Criteria
The use of an adequate optimization solver enables to minimize transportation costs by consolidating shipments into loads that minimize the total mileage and the usage of transportation space.
The solver considers ALL transportation needs.
The solver uses real carriers rates and routes, and considers all detailed transportation constraints.
The solver dynamically selects cross docking locations and activities.
The solver enables dynamic merge-in-transit to ensure one single delivery to the customer while minimizing transportation costs.
The sequence of optimization strategies is regularly fine tuned by performing what if analysis.
To wrap up this module, let us now review the list of excellence criteria attached to the transportation scheduling process.
The first criterion insists on the fact that no transportation scheduling optimization can be obtained without an optimization solver.
The second criterion emphasizes the need to apply this solver globally on all transportation needs, as opposed to a piecemeal approach.
The third criterion focuses on the need to use detailed transportation data and not aggregated data and to consider all the detailed transportation constraints, such as specific type of vehicle needed to ship specific products, state or country legislation which prevents drivers from driving more than a certain number of hours in a row, etc. This is essential to guarantee that the transportation plan is realistic and fully executable.
The fourth criterion reminds us that the optimization solver must be able to dynamically select the cross-docking locations (which is a capability that few solvers properly handle).
The fifth criterion highlights the need for a “merge in transit” capability, as just described.
Finally, the sixth and last criterion states the need to review on a regular basis the sequence of the optimization strategies contained in the global solver, because the sequence in which the strategies are applied has an obvious impact on the final result of the solver.