Route optimization is the quickest and easiest way for a last-mile delivery business to get more efficient routes and cut costs. Despite its well-proven power to reduce mileage, many businesses are still stuck in their ways of manual route planning.

We believe that this is because the term route optimization is ill-understood as it can mean different things to different people. It conjures up an image of mathematicians sitting in a room full of formulas on whiteboards, which gives it an air of scary mystique.

The goal of this guide is to dispel the mystique and provide clarity on the topic of route optimization, through a practical lens of small and growing delivery businesses.

We'll also discuss the problems with conventional route optimization and introduce a new concept called Intelligent Route Optimization to address these.

What is route optimization?

Route optimization is the process of finding the shortest, most cost-effective routes between multiple destinations, while meeting real-world needs and business constraints.

If all you have is a dozen addresses and a single driver, a human route planner can do the job decently well. But as your business grows to a hundred deliveries per day with multiple drivers, the route planning puzzle gets extremely complex.

Route optimization software takes all the information needed to plan a round of deliveries — addresses, time windows, driver schedules, vehicle capacities, and more — and automatically creates highly efficient routes in a matter of seconds.

Why does this matter?

In a delivery business, inefficient routes have a direct financial impact. They impact fuel use, vehicle wear and tear, driver wages, and the number of deliveries that can be made in a day. So less distance driven = lower fuel costs and increased profitability.

There are wider social and environmental benefits to route optimization, too. Route optimization can help relieve traffic congestion and reduce fossil fuel consumption.
A map with three optimized routes.A map with delivery addresses plotted on it, ready to optimize.
How do you plan routes to visit all these places in the most efficient way? Route optimization!
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A short history of route optimization

A complete guide isn’t complete without a history class, so we’d like to bring you on a brief journey of route optimization’s origins in academia. You are free to jump to the next section on route optimization in today’s world.

For as long as humans have been moving around the world, they’ve tried to find ways to do it more efficiently. Our ancestors built their first roads following animal tracks, to take advantage of efficient routes that had evolved over many years.

Starting with Leonhard Euler’s solution of the Königsberg bridge problem in 1736 (spoiler: there is no solution), mathematicians have tackled increasingly complex routing problems.

Front-page of the first paper that describes the Traveling Salesman Problem.
This 1949 research note from the Rand Corporation is the first recorded use of the phrase “traveling salesman problem” in an academic publication.
Picture of the Seven Bridges of Königsberg problem.
The Seven Bridges of Königsberg problem: How do you find a route that crosses every bridge, once and only once?

In the 20th century, the Traveling Salesman Problem (TSP) dominated: Given a list of cities, what is the shortest possible route between them that visits each city exactly once and returns to the starting point?

Mathematicians tried various approaches to tackling the problem throughout the 20th century— in the 1950s and 1960s the RAND corporation even offered prizes for solving it.

To this date, the TSP remains an unsolved problem – at least in the sense of finding the optimal route for problems of any size. Instead, many creative meta-heuristics have been developed to approximate a good-enough solution.

In present time

The Traveling Salesman Problem remains one of the most-studied challenges in computer science, along with variations that consider multiple routes like the Vehicle Routing Problem (VRP) and the Pickup and Delivery Problem (PDP).

And that’s just the start of the variations. When you consider constraints like time-windows or vehicle capacities, you now have the Vehicle Routing Problem with Time Windows (VRPTW) and the Capacitated Vehicle Routing Problem (CVRP). You’ll even find academic papers using terms that sound like you’re cursing: MDHFVRPTW – the Multi-Depot Heterogeneous Fleet Vehicle Routing Problem With Time Windows.

No wonder route optimization isn’t the most popular kid on the block!

Bill Cook lecture on the travelling salesman problem.
A 2021 lecture by Bill Cook explores the mathematics of the Traveling Salesman Problem.
Image of the Travelling Salesman Problem (TSP).Image of the Travelling Salesman Problem (TSP).
Image of the Vehicle Routing Problem (VRP).Image of the Vehicle Routing Problem (VRP).
Image of the Pickup and Delivery problem (PDP).Image of the Pickup and Delivery problem (PDP).

One of the problems of academia is that it incentivizes scientists to publish ever-greater numbers of academic papers. And the best way to get published is to tackle a new variation of the problem, or improve on an existing algorithm by finding more optimal routes. This has led to a huge body of literature covering a plethora of variations with creative acronyms. Chasing the academic goal of finding the best route has led to numerous hyper-optimized, tailored algorithms.

But who cares if a route solution is 99% optimal versus 99.5% optimal? Especially if the 99.5% solution takes 22.6 years of compute time to calculate! That’s how much computation power was needed to set the world record on a TSP problem with 15,112 cities – with no obvious practical benefit.

Did you know?
In computer science terms the routing problem is known as an NP-hard problem: the number of permutations grows exponentially as the number of stops increase. With 57 stops, the number of possible routes is a ridiculous number – 10^75 or a quattuorvigintillion. To put that into context, astronomers estimate the total number of stars in the universe at between 10^22 to 10^24. No wonder humans are bad at route planning!
XKCD comic on the NP-hard routing problem.

Route optimization in the real world

Large corporations like UPS or FedEx have spent billions employing huge teams of academics to develop their own in-house algorithms trying to find the best routes. We wanted to bring the power of route optimization to small and medium businesses in an easy and accessible way.

First, we needed to tackle the branding problem so we coined the term Route Optimization back in 2012 to consolidate the various academic terms being used at the time. The few commercial routing softwares that existed before us called themselves “TSP and VRP solvers” or “Multi-stop Routing and Scheduling Optimizers” to name a few. We started marketing the term in earnest in 2015 and you can see on Google Trends that the term Route Optimization has increased 300% in popularity as compared to 2010. But even today, it is still a relatively little-known term.

Secondly, we developed an easy-to-use web application that anyone can learn in minutes – as we’ll see in the section Getting started with route optimization. Existing solutions in 2012 were very complicated for people without a background in Computer Science to get started with. Fast-forward a decade, now there are many good software options on the market – here’s a review of the Best Route Optimization Software in 2023.

And finally, the algorithms needed to account for real-world factors, because the real world is much more complex than the academic world (unfortunately). For one, academic papers describe routes on a blank piece of paper (called a Cartesian plane) whereas real delivery drivers need to follow the road network, with varying traffic patterns throughout the day and week.

What’s more, there are soft human considerations to route optimization that are also important to keep your drivers happy. We'll expand on this concept further in the section on Intelligent Route Optimization.

Graph showing the increasing popularity of the search keyword "route optimization".
Route optimization as a search term on Google since 2010 has increased by 300%
Other soft human considerations to route optimization that are also important:
Traffic considerations
Who likes to be stuck in traffic? Dispatchers often have tribal knowledge of local traffic patterns. You can easily waste hours if you don't incorporate this in your route planning.
Balanced Routes
Optimizing simply by shortest distance can also result in imbalanced routes that will be unfair to your delivery drivers. You may be paying contract drivers by number of deliveries or total work time.
Clean Clusters
Overlapping routes that criss-cross can also cause driver frustrations as it is perceived to be inefficient (even though mathematically it might sometimes be shorter, it is not always practical).

Algorithms vs humans in route optimization

In our survey to 11,246 businesses, we discovered that 72% of them still plan routes by hand and did not leverage route optimization software. It makes sense for small businesses. It's free. But is it really free when you're spending your precious time solving route puzzles? Besides, how good are your routes, really?

Perils of manual route planning

Richard Seymour is the Managing Director of Mount Zero Olives, an Australian business producing high-quality olive oil. For many years, they relied on tribal knowledge to plan delivery routes, but Richard recognized the problem when that process failed.

Most small businesses that are just starting out will use Google Maps as a route planner or create delivery routes in Excel. While these are familiar tools and a good way to get started, it still requires a lot of manual work and is very time-consuming.

Stringing together a manual route planning process requires tribal knowledge. In Richard's situation, his main route planner was out sick one day, and everything just fell apart – nobody on his team knew how to plan routes.
We discovered Routific out of desperation. All the knowledge of routes and deliveries was in one particular driver’s head. And he wasn’t around. He was out sick.
Richard Seymour
Mount Zero Olives

In present time

Using commercial route optimization software, anyone can plan delivery routes. And when you do, you’ll not only save yourself the headache, you might also reclaim one to two hours of your life.

Even if a human being decides to spend two hours of their time creating routes, how good are they?

Route optimization algorithms have proven to create routes that are much more efficient than human route planners. In a 2017 academic study, researchers invited participants into a lab and presented them with a route planning puzzle on a piece of paper and gave them one hour to complete.

On the easiest variant of creating 4 routes to 31 stops (the above picture), subjects drew routes that were on average 9.8% longer than the optimal solution. Not too bad. On a slightly more complex variant for 6 routes and 39 stops, subjects were on average 20.5% longer than the best route.

You can see that human route planner performance rapidly degrades as the size and complexity of the route planning problem increases.

The other thing to note is that while 20.5% shorter routes may sound little, for a delivery business that delivers to a hundred customers a day, this can easily translate to thousands of dollars saved each month! For larger delivery operations with thousands of deliveries a day, the savings scale into the hundreds of thousands a year.

Lab-based puzzles on a sheet of paper are much simpler than real routing puzzles that delivery businesses face. As mentioned before, real delivery businesses need to keep the real road network into account (as opposed to drawing straight lines). Also, the only constraint in the above experiment is capacity, whereas in the real world, businesses often have to consider delivery time-windows, different vehicle types, and driver preferences to name a few.

Therefore, it is conservative to say that an algorithm can easily outperform human route planners in the real world by 20%~30%.

Image of academic study that measured how bad humans are at manual route planning.
The lab-based puzzle had the above picture with the following prompt:
"For this problem you have 4 trucks. There is a total of 370 units to collect averaging 93 per truck. Draw 4 routes that visit each and every one of the sites starting from the depot (the green dot), making sure that each truck returns to the depot with no more than 100 units on board. Remember to change pen colour after drawing each truck route and route the number of the truck (from 1 to 4) next to the route."
We spent about an hour rewriting our routes every time we added a new pick-up point to our network. We used maps, and a lot of manual calculations. Routific’s AI solution is smart and fast. We quickly understood this was the best way.
Thibaut Martelain
Marchè Second Life
A portrait of Thibault, happy Routific customer.

Case study: Spring Hope Food

We ran our own man vs machine experiment with the Spring Hope Food Drive. Landon spent 4 hours trying to organize his routes by hand using his usual method. He then uploaded the same data to Routific to optimize delivery routes – which took him only 3 minutes. The results were staggering: his drivers were able to get the same deliveries done driving 37% fewer miles and with 8 fewer cars.

Just like with chess, humans stand no chance against route optimization algorithms. With today’s technology, there's no good reason why one should still plan routes manually. Route optimization algorithms can take care of the route planning headache, do it in minutes as opposed to hours, and find routes that are 20%~40% shorter, all of which translate directly to your bottom line.

Infographic comparing manual route planning with route optimization, reducing 8 vehicles and saving 37% in mileage and fuel.
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Intelligent Route Optimization

Intelligent Route Optimization considers the human elements of route planning – keeping your drivers happy – whereas regular route optimization just tries to minimize driving time or distance. Being in the market for over a decade, we learned from our customers that a mathematically optimized route may not be practical for various reasons. They end up spending an hour manually fixing the routes until they get to a point where they are ready to dispatch.

This obviously defeats the purpose of using a route optimization algorithm.

Below are the major reasons why some businesses are reluctant to adopt route optimization software, because they typically can do better than a dumb algorithm.

Traffic-aware routing

Most route optimization algorithms do not take time-of-day traffic into account. Route planners know that certain roads are to be avoided at certain times. Using tribal knowledge of traffic patterns, they will edit the routes until they’re happy.

Some routing software may advertise that they incorporate traffic, but usually they just pull the traffic data from Google Maps and apply it in retrospect to the route solution. Admittedly, this is what we did back in 2015 ;-) But we learned that this isn’t good enough, as it can break constraints and result in inefficient route sequences.

Intelligent Route Optimization uses AI technology to predict traffic patterns that vary depending on time-of-day and day-of-week as a direct input to the algorithm, so that the algorithm can optimize with this in mind.
Graphic of traffic jam during rush hour vs non-rush hour.

No more spaghetti routes

“Drivers hate seeing each other on the road. They have a fit! They all talk to each other and show each other their routes. They get really upset,” one customer told me.

This was a large-scale operation that uses an expensive routing solution, yet employs eleven manual route planners to manually create clean clusters to keep their drivers happy.

Drivers also dislike getting off the highway for just a couple stops. They prefer clean clusters where they drive a long leg in the beginning and end, so they can focus their work in a dense area.

Spaghetti routes may be shorter mathematically in some cases, but they are not always better in the practical sense. Here’s an image that illustrates the difference:
Drivers have to get off the road, do two stops, then keep driving – they hate it!
Headshot of Joe, route planner at a courier company.
Joe Wemert
Becool Couriers
Spaghetti routes are routes that criss-cross a lot like a bowl of spaghetti.
Clean clustered routing creates tight territories and happy drivers.
These routes were created with the same set of stops and drivers; the first picture is from a competitor and second one is from Routific. While the competitor had slightly shorter routes, you can see them overlap with one another like a messy spaghetti bowl. In a few parts of that picture you can see three drivers being routed to the same area (see circled).

You can also see the teal-coloured starting in the south and snaking up north, doing single deliveries along the way, passing by three colleagues along the way. Imagine the driver’s look on their face at the end of the day!

Driver Familiarity

Clean clusters will definitely make your drivers happy. But that’s not the only thing you can do. Drivers also tend to prefer to stick to similar regions. As drivers get familiar with the roads, parking situations, and clients, they get more efficient over time. There’s a learning curve. And when drivers get more efficient, they feel that they’re doing their best job for your company, which means that they’ll be happy and stick around.

In a research led by Paolo Intini, he showed that drivers can drive 10% faster on roads they have driven on more than five times.

If on top of that you shave off a few minutes of finding the buildings, parking, and delivery location for a particular customer, your deliveries will be even more efficient – while reducing the error rates.

Happy drivers, fewer errors, lower cost-per-delivery, a more profitable business!
Drivers can drive 10% faster on roads they have driven on more than five times.
Headshot of Paolo, researcher in driver speed in familiar territories.
Paolo Intini
Polytechnic University of Bari
A map showing a route and the driver's familiarity with that territory.
This is why many delivery businesses still spend hours manually tweaking the routes they get from routing software – to try and keep drivers in the same territory. Some may even resort to drawing driver territories, but that results in hard boundaries that harms your overall route efficiencies.

Intelligent Route Optimization incorporates drivers’ experience into the route solution intelligently, without sacrificing overall route efficiency.

Balanced Routes

Route optimization algorithms are designed to minimize a given fitness function, which typically consists of total drive time or distance. Aside from looking like spaghetti, as shown above, they may also be imbalanced. It is not practical to assign a driver fifty deliveries while another gets only ten.

If you pay your drivers by the number of packages, you want to balance the routes by number of deliveries. If you pay them based on the hours worked, you want to balance the routes by shift time. Even if your drivers are salaried, they would still prefer to be treated fairly.With smart auto-balancing everyone gets to go home early!

Accurate Geocoding

When you geocode addresses on a Google Map (i.e. you upload an address and Google translates it to coordinates) the pin sits right on top of the building and navigation typically goes to the front door. Instead, you may want to route to the loading bay in the back. These are often one-way streets, so your routing can get out of whack.

That’s the best case. In the worst case, the pin is put erroneously on the other side of town, leading to tons of frustration and wasted time, when the driver arrives there only to realize it’s the wrong address.

Make sure you have clean addresses, or choose routing software that has smart geocoding with fallbacks and highlights potentially risky addresses for manual verification.

Getting Started with Route Optimization

If you are planning routes manually on a spreadsheet – and assuming that the address data isn’t gibberish – it’s really easy to get started with route optimization software. We’ll be using Routific as an illustrative example, but these three easy steps can apply to any routing software.

Our philosophy is that AI should not aim to replace human dispatchers. Instead, we liken Routific to an Iron Man suit – it gives the dispatcher superpowers! A single dispatcher can now manage a fleet of twenty drivers easily, whereas previously you needed to hire more people.

The accuracy of geocoding is vital. Sending a driver to the wrong location on the other side of town can be extremely frustrating and costly.

Good routing software will have very accurate geocoding processes and warn you about potentially faulty addresses to give you a quick way to review and fix those.
Most routing software will allow you to upload a spreadsheet of addresses. The addresses are then interpreted in a process called geocoding and plotted on a map.

Routific screenshot of uploaded stops using spreadsheets and plotted on a map

The next step is to set up your delivery fleet. At a minimum, you need to specify the number of routes, the start locations, and the route shift times.

With Routific you can choose to spread the deliveries across a pre-defined number of routes, or let the algorithm figure out the fewest number of routes.

You can also specify a capacity on your vehicles to make sure routes are not overloaded – or assign a driver to a territory they're most familiar with.

Routific screenshot of driver setup and route constraints.

With the data set up, you’re ready to create your first set of optimized routes!

Human brains are wired to be skeptical of algorithms and AI, especially when you’ve been doing it manually for years. That’s why we’ve created an intuitive and powerful route planning interface that makes it easy to inspect routes and make changes, should you feel the need.

Over time, most route planners learn to trust the algorithm and let it do most of the heavy lifting.

Routific screenshot showing optimized routes on a nice dashboard with routes on a timeline

Choosing route optimization software

If by now you are convinced that your business can benefit from route optimization, the next natural question is: which route optimization software is right for me? There are so many out there: Capterra’s Route Planning Software category lists 245 route optimization solutions!

Capterra is a public reviews site where real users can rate software and leave feedback and testimonials. One thing to watch out for is Capterra’s list is by default sorted by “Sponsored” which means that whoever pays the most, gets shown on top. Make sure that you change it “Highest rated” to sort the list in a more useful way:
Screenshot of Capterra's Route Planning Software category, highlighting that you should sort by "Highest Rated" instead of "Sponsored".
As the authors of this guide, we would of course be delighted if you signed up for a free trial of Routific. However, keeping the best interest of our audience in mind (i.e. you!), we recommend that you look at a few options and do your own research. To make your life easier, we’ve also done our own research and shortlisted a few of our favorites in the article: Best Route Optimization Software In 2023.
Delivery van loaded with packages.
Source: anushkaniroshan // Shutterstock

5 ways optimizing delivery routes could help the environment

As e-commerce booms, more products are shipped around the world. Global e-commerce sales ballooned from $1.34 trillion in 2014 to more than $3.35 trillion in 2019, according to the International Trade Administration. And that was before the COVID-19 pandemic online shopping surge hit, which drove unprecedented e-commerce growth: In a span of just three months, online shopping grew at the same pace as the previous 10 years. Pandemic-related shifts in consumerism have since driven global e-commerce above $5.4 trillion as of 2022, with projections expecting the worldwide market to reach $6.39 trillion by 2024.
Unfortunately, this new landscape of delivery has contributed to a near-unprecedented level of environmental pollutants. The transportation industry uses tonne-kilometers to measure the movement of 1,000 kilograms (about 2,205 pounds) of cargo over a distance of one kilometer (about .62 miles). In 2020, almost 140 billion tonne-kilometers of cargo were transported worldwide—26.8 billion via roadways—resulting in more than 3 billion cumulative tons of carbon dioxide emissions.
Transporting shipments by road may offer significant opportunities for sustainable transformation. Options range from the simple and intuitive—such as coordinated delivery timing or sharing warehouse and vehicle spaces—to the technologically innovative, like autonomous vehicles, deploying drones, or sending out delivery robots.
Using government sources, sustainability reports, and industry publications, Routific compiled a list of five ways optimized delivery routes can help the environment. Read on to learn how changes can be made along the supply chain to reduce the global footprint of the expanding e-commerce industry.
Couriers with boxes on the ground.
Source: Andrey_Popov // Shutterstock

Avoiding unbalanced route lengths—and empty vehicles

The transportation sector is responsible for 16.2% of all greenhouse gas emissions across all industries. Within that sector, road freight vehicles account for 40% of all transportation-related GHG emissions, which translates to 4-5% of all global CO2 emissions. Many freight vehicles take routes that are not optimized for efficiency—traveling long distances with comparatively little cargo or even none at all—thus squandering fuel.
There are a variety of ways to balance out routes to make them more carbon-efficient. Some companies are exploring opportunities to establish collection points to allow for a single route to result in a high-yield delivery. Others are seeking collaboration between companies to co-load and share vehicle space, thereby maximizing a vehicle's capacity and avoiding low or empty journeys.
Additionally, narrow delivery windows of only a few hours can also result in a route with a light load. They often force vehicles to depart at a certain time, even if there are only a few packages in tow. Widening delivery windows can allow freight vehicles to carry out more deliveries while expending less fuel.
Transportation truck driving on a road.
Source: Milos Muller // Shutterstock

Prevent idling in traffic

Every year, the average freight truck spends around 1,000 hours idling. All told, this results in burning millions of gallons of diesel needlessly. Though much of this latent time occurs when drivers take necessary breaks to sleep or eat, a great deal happens when vehicles are stuck motionless in traffic.
To avoid this and reduce the amount of wasted fuel, drivers could rely on real-time GPS systems, which can alert them to heavily congested areas and reroute them along speedier roads. Employing night-time deliveries could also reduce freight traffic by 15%.
There are also a variety of idle reduction technologies designed to balance the internal engine heating and cooling that otherwise result in engines burning more fuel than necessary. These include energy-efficient HVAC systems and solar panel systems. In addition, automatic engine start-stop systems are already available in most new passenger vehicles and have demonstrated emissions reduction.
Two couriers handing packages to load the van.
Source: Gorodenkoff // Shutterstock

More deliveries per route

Optimizing the number of deliveries that can be made on a single route can save fuel and maximize energy efficiency. By encouraging companies to combine warehouses and loading facilities, they can better fill up a space's capacity, ensuring more goods and resources are ready for loading and delivery. Businesses can also use work-sharing delivery vehicles to ensure a single route meets its full potential capacity of goods delivered per route.
Another strategy could be consolidating deliveries to a few key areas, thereby reducing delivery emissions by as much as 30%. Package pickup lockers, like those used by Amazon, and shops that accept packages for multiple recipients could reduce congestion by up to 18%.
Loading up packages in a delivery van.
Source: BigBlueStudio // Shutterstock

Optimizing last-mile delivery

"Last-mile" or "final mile" delivery refers to the final leg of a product's journey when transported from the delivery vehicle to the consumer's front door. This delivery aspect often results in the most environmentally damaging practices, as consumers increasingly demand near-instant deliveries. Speedy deliveries put pressure on companies to prioritize speediness over fuel efficiency and can mean sending out a driver with a light load simply to meet a deadline.
Last-mile delivery is expected to account for a 36% increase in delivery vehicles in the world's 100 largest cities by 2030, resulting in delivery emissions rising by almost one-third. One researcher from the Hellenic Institute of Transport in Greece found that 20-30% of a city's overall CO2 emissions are already the direct result of last-mile deliveries.
Unlike a large cargo truck transporting many tons of goods to one location like a warehouse, last-mile deliveries require fleets of smaller trucks to hand-deliver each product to someone’s doorstep, adding up to many cumulative miles over individual trips. However, while final-mile deliveries present the most significant environmental damage during the product shipping process, they also pose the largest opportunity for sustainable improvement.
Stockpiling products to have them ready for last-minute orders or investing in carbon offsets (i.e., planting trees or installing solar panels to 'gain back' the CO2 emitted) can balance out negative impacts while still keeping consumers satisfied with delivery times.
Finally, customers shouldn't be underestimated. MIT researchers found that showing trees to buyers helped them visualize the carbon footprint of their purchases, motivating them to opt for less-urgent delivery times. Using a similar technique at checkout could possibly help companies reduce their last-mile emissions by 25%.
A pallet loaded in a trailer.
Source: Siwakorn1933 // Shutterstock

Launching supply chain technologies

There are a variety of developing technologies that can make packaging, shipping, and delivery more sustainable overall. Within warehouses and loading docks, digital freight matching services can optimize delivery by matching vehicles with the most efficient shipment load and route for their fuel capacity.
Once parcels hit the road, carbon-saving transport systems can be invaluable in reducing emissions. Electric vehicles with intelligent transport systems can alert manual drivers or self-driving vehicles to adapt their routes in order to save fuel. For more automated modes of transportation, some companies are looking into delivery drones and even robots. And some companies are taking a two-wheeled approach, as a single e-cargo courier bike alone could save 101,000 kilograms of CO2 per year compared to a delivery vehicle.


We took you on an academic tour of route optimization and its origins, how it crossed the bridge into real-world applications, and in the process hopefully convinced you that route optimization is far superior to manual route planning.

We showed that route optimization can reduce mileage by 20%-40% and how it is the single most impactful lever you can pull overnight to increase the gross margins of your delivery business. We also reviewed the environmental impact of adopting route optimization. Aside from route optimization, it’s important to review your entire delivery management process that may benefit from automation as well.

Yet, many businesses stick to manual route planning. Those that do use route optimization software often still spend hours tweaking the routes to their likings. With Intelligent Route Optimization this is no longer necessary, if it considers driver happiness and route acceptability. Among other things, Intelligent Route Optimization is traffic-aware, creates non-overlapping routes, and provides smart recommendations as the system gets to know your drivers.
Portrait of Marc Kuo.
Marc Kuo
Marc Kuo is the Founder & CEO of Routific, a route optimization platform for growing delivery businesses. With over a decade of experience in the last-mile industry, he has advised hundreds of delivery businesses on their route planning and delivery operations.
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Frequently Asked Questions

Can Google Maps optimize my route?

No, Google Maps cannot optimize your route. Google Maps is created for consumers who travel from A to B. But when presented a list of addresses to visit, Google cannot give you the optimized sequence of stops.

Here's an article that describes the relationship between route optimization and Google Maps.

How does route optimization software work?

Given a list of addresses, drivers, and constraints, route optimization software will calculate the best routes possible and present them on a map, and in the case of Routific, on a timeline view as well. You can then inspect the routes and make manual adjustments as you see fit.

What are the benefits of route optimization?

1. Automate route planning: the amount of time you spend manually planning routes every day can be better spent on growing your business.

2. Optimize routes: with route optimization you can find 20% to 40% shorter routes, which directly reduces your cost per delivery (which is made up of fuel costs and driver wages).

3. Reduce risk of tribal knowledge: most business owners that are just starting their delivery business often take on the burden of manual route planning. Over time, they acquire tribal knowledge on manual route planning. With route planning software, anyone can do it. And the business owner can finally take a vacation.

4. Tracking KPIs: with route planning software you get the benefit of visibility, how much you’re driving each day, your cost per deliveries, how much mileage each car has accumulated, which makes fleet management easier too.

5. Real-time driver tracking: most route optimization solutions come with a mobile app with GPS tracking, so you know where your drivers are in real-time.

Does Route Optimization take traffic into account?

Most route optimization software do not take traffic into account when creating the routes. They typically rely on average road speeds using mapping data from OpenStreetMaps. We discovered that the lack of traffic consideration leads to overoptimistic ETAs from OpenStreetMaps, which then leads to unrealistic routes your drivers cannot follow.

With Routific’s Intelligent Route Optimization, we do take traffic into account. We have trained 179 Machine Learning models across the world to predict traffic patterns, which we then incorporate into the route optimization algorithm. We have seen ETA accuracies improve significantly – sometimes as much as an hour on an 8-hour route.

Are there any free route planning apps?

Yes, there are many free route planning apps available, but they each have limitations.

We have written an in-depth review that lists the 7 Best Free Route Planners in 2023.

Does route optimization software also include dispatch and customer notifications?

Routific’s route optimization software also includes delivery management functionality such as dispatching, live GPS tracking, and customer notifications.

Many other route optimization softwares also have this, though not all.

Is there a standalone Route Optimization API?

Routific has a standalone route optimization API, accessible via a stateless REST API, with wrappers available for Node, Ruby, and Python.

We also have APIs available that allows you to connect to our full end-to-end delivery management platform.

What's the difference between route planning and route optimization?

Route planning is the entire process that starts from having a list of addresses, creating a multi-stop routes (either manually or use route optimization algorithms), inspecting and editing those routes, all the way to dispatching those routes to your drivers, ideally on their mobile app.

Route optimization is a part of the route planning process, which seeks to automate the process – so you spend less time route planning – and to find the most efficient route possible, thereby cutting mileage and fuel costs.

For more details, see Route Planning vs Route Optimization.