Vrp solving software

Imagine a company that needs to visit its customers in a city made up of identical rectangular blocks. A diagram of the city is shown below, with the company location marked in black and the locations to visit in blue. To set up the example and compute the distance matrix, we have assigned the following x - y coordinates to the locations shown in the city diagram : [ , , location 0 - the depot , 0 , location 1 , 0 , location 2 0, 80 , location 3 , 80 , location 4 , , location 5 , , location 6 , , location 7 , , location 8 , , location 9 , , location 10 , , location 11 , , location 12 , , location 13 , , location 14 0, , location 15 , ] location 16 Note that the location coordinates are not included in the problem data: all you need to solve the problem is the distance matrix, which we have pre-computed.

You only need the location data to identify the locations in the solution, which are denoted by their indices 0, 1, The main purpose of showing the location coordinates and the city diagram in this and other examples is to provide a visual display of the problem and its solution. But this is not essential for solving a VRP. However, there is no special reason to use this definition.

You can use whatever method is best suited to your problem to calculate distances. As in the TSP example , the following function creates the distance callback, which returns the distances between locations, and passes it to the solver. It also sets the arc costs, which define the cost of travel, to be the distances of the arcs. To solve this VRP, you need to create a distance dimension , which computes the cumulative distance traveled by each vehicle along its route. You can then set a cost proportional to the maximum of the total distances along each route.

Routing programs use dimensions to keep track of quantities that accumulate over a vehicle's route. See Dimensions for more details. The following code creates the distance dimension, using the solver's AddDimension method.

The method SetGlobalSpanCostCoefficient sets a large coefficient for the global span of the routes, which in this example is the maximum of the distances of the routes. This makes the global span the predominant factor in the objective function, so the program minimizes the length of the longest route. Alternatively, you can first save the routes to a list or array, and then print them. See the TSP section for a description of that code. What's new is the distance dimension , described above.

The complete programs are shown in the next section. When you run the programs, they display the following output:. The locations in the routes are denoted by their indices in the locations list. All routes begin and end at the depot 0. The diagram below shows the assigned routes, in which the location indices have been converted to the corresponding x - y coordinates.

The section shows how to use the Google Distance Matrix API to create the distance matrix for any set of locations defined by addresses, or by latitudes and longitudes. You can use the API to calculate the distance matrix for many types of routing problems. Here's how to obtain one. Example As an example, we'll walk through a Python program that creates the distance matrix for a set of 16 locations in the city of Memphis, Tennessee. The distance matrix is a 16 x 16 matrix whose i, j entry is the distance between locations i and j.

Secondly, fleet and transportation management systems are often stuffed with numerous default, baseline functions. If some of them remain unused which is quite likely , they will just confuse your delivery managers and make their work harder.

Unfortunately, there is no one-size-fits-all option that would simultaneously cover and satisfy the needs of all businesses. To make the right decision, review the logistical processes of your company, calculate the budget, and consult with a professional business analyst. This is another important choice you have to make in order to solve the VRP with the help of technologies.

In this case, using some off-the-shelf route optimization systems will help you get a better understanding of your requirements and give you a sense of what feature set you might want to or will want to ultimately have. Here are some popular off-the-shelf tools for route optimization:.

Alternatively, your development team may use OR-Tools which are open-source customizable Google tools for route optimization. However, if your business heavily relies on quality deliveries e. On top of that, such a solution may be integrated with your existing enterprise systems so your entire business will be streamlined and connected.

This means that a feature-set should be the first thing you should pay attention to when choosing or deciding on creating such software.

Another crucial aspect of route optimization software is the ability to include vehicle restrictions and set customer preferences. In general, the more constraints a system can solve the better.

We have already mentioned some advantages of solving the VRP with route optimization software throughout the article. These days, there is quite a wide variety of available ready-made VRP software solutions on the market. We would like to discuss some of the most popular and frequently used vehicle routing software that were defined as qualitative by Gartner.

This is one of the most popular ready-made vehicle routing software that provides proper management of any type of deliveries all over the world.

Among the key features this cloud-based solution offers that we would like to mention are:. Appian is the provider of safe transportation that aims to provide improved customer experience for the company they deliver from as well as for their services. This solution implies the availability of their carriers and transport like fleets so that means that they not only help to organize and monitor the delivery process but they perform the order shipments on their own.

Among the main features that we would like to note are:. Paragon is tasked with optimizing the vehicle scheduling and routing in the way of providing specific delivery route optimization algorithms and shipment planning.

We also would like to mark the core function that Paragon offers, and they are the following:. Compared to the ready-made solution, the development of your custom vehicle routing solution seems to be quite complicated and long-lasting. However, you may come to understand that your custom software is an investment in your future business development.

Once you implement your system, it can always be changed up to your current demands, updated corresponding to the latest tech trends on a software market, easily scaled and expanded by functionality, etc. The final cost depends primarily on the range of specifications and general scope of work that is known at the end of the development process as there is a high likelihood that project details will be changing during the development life cycle.

We also would like to ensure you that our estimation approach is highly detailed, clear, and easy to understand. We know how to keep the project under your particular budget. Hence, we would like to show our estimation template and how thorough it actually is. Due to the defined scope, a software project is divided into several large pieces that are called sprints when each sprint is discussed thoroughly, planned, split into tasks that are assigned to particular developers.

Talking about this vehicle routing software solution, the development process of MVP can take at least 3 to 4. Let us say a few words about the development team this type of software will need. We also would like to emphasize the importance of the role of the Scrum master as this team member is responsible for managing and tracking every stage of the development process, keep the client informed about the changes in the development life cycle and make sure that all tasks are executed appropriately.

You may ask why we use Scrum methodology as a core. Scrum methodology suits all types of software projects and surpasses other methodologies because with it:.

A vehicle routing problem is a common challenge faced by many businesses. Modern supply chain and logistics processes are quite complex while customers always expect to receive high-quality services. A custom vehicle routing software is tasked with considering all your demands to boost the productivity of the workflows according to their specifications. GBKSOFT is here to help you define the weak sides of your company and find the right solution to turn them into strengths with the use of custom vehicle routing problem software.

Ready to solve your vehicle routing problem with a robust software solution? Nothing can be better than getting a review from our happy clients who recommend us and trust us their business. As the name suggests, this approach proposes to compute every possible solution until one of the bests is reached.

Heuristic methods perform a relatively limited exploration of the search space and typically produce good quality solutions within modest computing times. Gradually build a feasible solution while keeping an eye on solution cost, but do not contain an improvement phase per se. The problem is decomposed into its two natural components: 1 clustering of vertices into feasible routes and 2 actual route construction, with possible feedback loops between the two stages.