Lowering Packing & Warehouse Costs with Route Planning

Route planning can lead to additional savings at the depot or warehouse

Optimal route planning that takes into account vehicle capacities for deliveries (and/or pickups), both from the depot and intra-route pickups and drops-offs, can vastly improve efficiencies at the depot or warehouse leading to time and cost savings across the board.

We've already seen in a previous article, how including vehicle capacities and deliveries within a route optimization can lead to better, real-world solutions that your business can reasonably achieve (as opposed to route planning without capacities that will inevitably require vehicles return to the depot at unknown intervals to load up or offload leading to a drastic increase in labor, time and money).

Ideally, route planning should be aware of your fleets' carrying capacity and ensure that optimal routes are planned in such a way that no vehicle is ever overloaded, and that no time is wasted sending vehicles to and from the depot/warehouse unnecessarily. If it can achieve that it can generate a packing slip (because it already knows which deliveries are assigned to which vehicle and the order in which they will be performed.) that can be shared directly with the warehouse/depot manager who then knows exactly how to pack the vehicles ahead of time.

Let's take a look at this in action.

Generating a Packing Manifest for Optimized Routes

Consider a schedule setup as follows:

Route schedule showing capacity requirements

As you see this is a fairly straightforward situation. We have two vehicles that can each carry 10 Crates - remember that capacities on Optergon are defined by the user and can be absolutely anything - a volume, giraffes, boxes, etc - we are simply using crates for the purposes of this example. Each of the locations have a delivery requirement from the depot. Looking at these you can probably see that there are a lot of deliveries, so one thing we might learn from this optimization is whether or not the vehicles have sufficient capacity to perform all the deliveries without having to return to the depot.

Here's the result:

Route plan showing vehicle capacity constraints

That might not look too exciting. Each vehicle is clearly doing a nice optimized route with all deliveries being completed without having to return to the depot. Let's email a packing manifest for each vehicle to the depot manager to see what our packing requirements are based on this route plan. To do that is simply a case of selecting the relevant vehicle trips and choosing Depot from the Email button, like so:

Email a packing manifest to the depot for optimized routes

A moment or two later the depot manager receives the following packing manifests for each of the selected vehicle routes. Here's where it gets interesting (hint: look closely at the capacity requirements for each vehicle at the depot):

Depot packing manifest for optimal route (White Pickup - Paris)


Depot packing manifest for optimal route (Red Pickup - Paris)

Both vehicles are packed to capacity. The optimal solution has shown that it is in fact possible to complete all the deliveries in one trip. In some senses this has shown how Optergon is a dual optimization system because it is optimizing both the routes and the capacities in order to generate the overall most efficient and lowest cost routes.

This result shows how important route planning (with capacities) actually is. It means that the warehouse can optimize its own workload and streamline processes because they are made aware of precisely how to pack each vehicle ahead of time, including the order in which to pack them. Not only will route planning save on labor, fuel & wear and tear costs for the vehicles, it will also save time and money improving efficiency at the warehouse.

Route Optimization API

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