Any company, regardless of whether it produces a product or provides services, is aimed at making a profit. Consequently, its strategy will necessarily set the task of reducing unproductive costs. One of the types of such costs is the cost of transport, logistics, movement of goods, people, etc. Any manufacturing company strives to locate its warehouses and logistics centers so that the distances to them are minimal. Any transport company that provides transportation services strives to plan routes in such a way as to minimize both its own costs and those of the customers.
Specialists in the field of logistics are constantly solving the problems of optimizing planned transport routes. Some of them themselves perform a large number of calculations related to the planned distances, time, and optimal routes. Such calculations are sometimes very complex and require certain mathematical knowledge and analytical skills. Some experts use the simplest programs that do not take into account many features when planning routes. And only the logistics API service copes better than other methods with the task of efficient planning of transport movements.
The transport cluster in its development rushes forward by leaps and bounds. The reason for this is the significant changes in the world economy and the rapid flourishing of integration processes. Geopolitics, as one of the most influential factors, also makes a significant contribution to the expansion and interweaving of transport chains. Because of this, each player in the world market of cargo transportation faces difficult tasks in the development of transport logistics. Logistics specialists, together with IT specialists, analyze global market trends and then extrapolate the information received to freight transportation processes.
We have already said that task number one for any transport and logistics company is to increase the efficiency and effectiveness of the processes associated with the planning and implementation of cargo transportation. In this regard, there is a constant search and application of more and more new optimization tools and methods. And it is transport logistics that is one of the driving forces of this process of continuous improvement. And these are not empty words, as transport logistics sees as its primary task the choice of such an option for transporting any cargo to the consumer, in which the travel time will be minimal, unproductive costs will decrease, and the cargo will be delivered on time and without damage. This implies a simple conclusion that any challenges facing transport logistics are challenges directly related to the optimization of the process of planning and carrying out the transportation of goods. As part of this activity, two optimization problems are considered the main ones – this is the determination of the shortest transportation route and the “traveling salesman problem”.
Imagine the work of a certain conditional transport company that is hired by several online stores to transport completed orders to customers. In addition to drivers of trucks, this company also employs logistics specialists who are just involved in route planning. Planning is carried out as follows: on the set day of the week, for example, by Wednesday, everything ordered by customers has been delivered to the central warehouse and is ready for delivery. The logistics manager starts planning routes for the truck driver who will need to take the goods the next day to customers at different drop-off points.
When planning a route, not only its profitability but also its optimality should be taken into account. In other words, the driver must leave with several orders from the central warehouse, call at each point of delivery of the order and return to the central warehouse. At the same time, there should not be repeated arrivals at the points. As we can see, such planning is inherent in the classical TSP (“traveling salesman problem”). Let’s remember that there are several solutions to TSP. Of these, the more accurate, but long and complex, are the “method of the simple sorting” and the “branch and bound method”. More close to reality and effective methods are heuristic methods. There are also several of them, we will name the most popular ones: “Clark-Wright method”, “ant colony algorithm”, “genetic algorithms method”, “nearest city inclusion method”, “nearest neighbor method”.
Returning to our example, we do not claim that the logistics manager will apply any of these academic methods. Maybe yes. But suppose he simply uses a computer program that sorts orders by truck and visualizes them on a map, taking into account the detours of all delivery points. Undoubtedly, the program is good, but it does not take into account, for example, such important planning attributes as the complexity or peculiarity of the route, the specific time of arrival at the place, and the actual situation on the roads. As we can see, in practice the problem of route planning is much more complicated than the classical TSP and, of course, the analysis of its solution should be covered not here but in a separate review.
So, how can a company optimize cargo transportation by the best way? We declare with full responsibility that the use of the distance matrix API (DMA) will allow you to plan routes profitably, efficiently, and in real traffic situations. Why is DMA so attractive?
Firstly, DMA is not a tool static in time, it is mobile and takes into account current road conditions, processing current information about traffic jams and the features of the traffic itself. And although the size of the DMA increases with the number of incoming orders, our matrix is characterized by a large dimension. If you are interested in the question of how accurate are the results obtained for your request for an upcoming route, then here you can be calm absolutely, since the DMA time and distance calculations of our service are comparable in accuracy to recognized market leaders, such as the Google API.
And, of course, DMA performs calculations taking into account the current situation on the planned route. Moreover, the creation of the same route for different modes of transport will be different. For example, the road features and restrictions for trucks are different from those for cars or buses, and DMA makes sure to take this into account in its calculations. The result of such an analysis will be the opportunity for you to make a completely reliable forecast regarding the time of delivery of goods to customers.
Attractive for the users of our service will be the fact that in the DMA calculations, it does not matter where in the world the company which carries out cargo transportation is located. Its truck routes can be domestic, intercity, or international, our service will provide an accurate and adequate answer to your request for distance and time.
Those users who are already working with a similar Google API service and wish to switch to our service should not be afraid of transition difficulties. All the necessary attributes that make up the formats of consumer requests and responses, both of one and another service, are maximally adapted to each other, which makes the transition of users from one service to another and back hassle-free and accessible. And by visiting our website, you can see for yourself this, as you will find a detailed description of the transition process itself.
Well, the absolute advantage of working with our service is a very convenient payment system for using its products. The absence of prepayment and obligatory credit cards, and monthly payment only upon the fact of used volumes are attractive conditions for any of our users. And for those who are interested in the details of the payment scheme, discounts, and other financial subtleties, we invite them to familiarize themselves with the relevant sections of the documentation of our service, as well as visit the news page and user forum.
So, based on even such a short review of DMA, we can conclude that this product of our service opens up new horizons for many transport and logistics companies, carriers, and all those who are interested in optimizing cargo transportation through geo-technologies and related software.