Transportation has become quite popular in recent years. Automated transportation optimization solutions support the process in most large companies to create shipments for the inbound and outbound orders. What exactly happens in this optimization? Without going into the mathematical formulation and objective functions, here is a functional picture of what these solutions do.
Load Optimization: Load optimization creates the optimal loads for the standard trailer sizes. These could be optimized using the expected weight of the shipments or volume, depending on which one presents the loading constraint. The main objective of this part of optimization is simply to maximize the weight or volume capacity usage of the trailers for the shipments built. The constraints while deciding on load optimization are generally the dates and routes — the solution must find orders that can travel together in the same window of time to successfully create optimized loads.
Route Optimization: Route optimization selects the best route to minimize the cost of transportation. This could be a route where the shipments can travel on long-haul rates for the longest part of the route or where the route is a combination of multi-modal transportation options so that the longest leg of the shipments travel on rail. The constraints for this step can be existence of rate-contracts, availability of routes, and so on for the solution to select optimal routes.
Resource Optimization: Resource optimization finally selects the carrier and the equipment that the shipments will travel on. The objective here may be to minimize the cost or simply ensure reliable pick-up & delivery dates. Constraints that play into this step are availability of valid carrier contracts & capacities on selected routes.
While the steps here provide a functional understanding of the process, different vendor solutions may implement them differently or simultaneously. In fact, best solutions are those that have the ability to model all three cases simultaneously so that the output is globally optimized which simply means that instead of trying to create best loads first only to find that no available equipment can actually carry them on required dates, these solutions consider all constraints simultaneously to produce results that are feasible and optimized for the orders.
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