One of the most powerful and valuable features of high quality route optimizations (other than efficiency and lower costs) is the ability to know whether a certain delivery schedule is possible given constraints on time and number of vehicles.
Optimal route plans for every delivery vehicle in the fleet drastically increase the probability of achieving same day deliveries - that might otherwise require additional vehicles or multiple days to complete.
For example, a growing business might plan to increase their fleet size in order to keep up with demand.
Cost based route optimizations are different from route optimizations that take into account distance only.
A cost based route optimization is useful in the real-world because it meets the business objective of any company trying to streamline costs and improve efficiency.
By contrast, a route optimization that only considers distance provides an attractive hypothetical result - good looking routes on a map. But that's about it. This is simple to demonstrate with an example.
Delivery planning and route optimization are vital for streamlining transport, labor and logistics costs in the era of free delivery and rising gas prices. So called "last mile" deliveries can consume up to 30% of the entire supply chain cost so it's a prime candidate for optimization. It's not without challenges. Even relatively simple route optimizations can be extremely complicated.
The Last Mile Problem has been around for a while now and has been a thorn in the side of any number of industries, from telecommunications to transport and logistics. In essence the transport version of the problem is this,
Last mile deliveries can incur up to 30% of all transport costs.
Essentially this means that, no matter where the product was manufactured or warehoused, and how far it has traveled, getting it to the customer's door from the nearest depot will cost almost a third of that entire trip.
For any business that needs to both pickup and drop-off deliveries during the course of a route (as opposed to the classic model of delivering from a single starting depot), being able to plan routes that can correctly cater for intra-trip pickups and drop-offs is essential. This requirement is a becoming more and more important as large companies grapple with last mile delivery costs. Last mile delivery companies tend to have numerous en-route pickup locations as well as drop-offs.
Real world route planning must take into account a range of costs associated with your fleet of vehicles in order to accurately portray optimal solutions based on the specific characteristics of that fleet. Any system that only takes only distance or time into account (but not both) is not going to be able to calculate the best possible solutions because it is ignoring half of all your cost generators. Consider a big truck that costs $2 per kilometer in fuel and wear and tear as well as $15 per hour in driver's salary.
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 retu
Constraints on vehicles used for pickups and deliveries is a hard fact of business. Some items might need to be kept in a cold chain environment. Others might require a forklift to be moved on and off the delivery vehicle.
Route planning & management relies heavily on time, but not always in the way you might think. Delivery planning software has to lower an entire fleet's overall cost to company - even if this means increasing the time and cost of individual vehicles for the greater good. As the old adage goes, "time is money" and saving it is not always straightforward. Generally, there are two types of time constraint that go into route planning:
  • Schedule time limits: When, and for how long, your fleet can operate (i.e.
Optimizing routes is hard. Especially when you have to produce solutions that businesses can use in the real world. This means taking into account what individual vehicles can and can't carry. After all, there's no point in letting one vehicle visit all the locations on your delivery schedule if it only has sufficient carrying capacity to visit one or two stops at a time. Incorporating carrying capacities into route optimizations can have profound effects on the type of solution you end up with.