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.
Cost based route optimizations are different from route optimizations that take into account distance only.
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. Computers have a very difficult time trying to calculate efficient routes even for extremely short routes with simple delivery requirements.
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,
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.
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.
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.
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. Managing any type of constraint on deliveries while minimizing costs is vital for virtually every transport related business.
Precisely what type of constraints your business encounters is often going to be fairly unique so it pays to have real flexibility when it comes to optimizing around these constraints.
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:
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.