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or a field service operative with 10 appointments and an eight hour shift, there are over 3.6 million possible ways to schedule these visits. It is impossible for a human to determine an order for the 'best outcome'. This begins with considering appointment locations and available skills and parts; and subsequently leads to driving routes as a major part of the instruction for the operative. For a dynamic route planning algorithm, however, a calculation can be undertaken in a matter of seconds. But what is an algorithm and why are no two the same?
Algorithms accompany us through our everyday lives. Google's algorithm decides which search results are displayed to us. Amazon's algorithms know which purchase recommendations to make to us. Our navigation devices, fitness wristbands, cars and household appliances are also controlled algorithmically in many hidden parts. In all of these cases, the majority of steps run in the background with minimal human intervention.
WHAT IS AN ALGORITHM? SIMPLY EXPLAINED
An algorithm is, simply put, a step-by-step instruction to solve a specific problem. Algorithms have their origin in mathematics and are used today primarily in computer science. An algorithm calculates the desired solution from the user's input. You can imagine an algorithm in its most basic form like a cake recipe (by following this 'instruction manual' step by step, you solve the problem).
In principle, software algorithms work in the same way. You require a cake, however each time you run the calculation the 'ingredients' are different. This is the input data. The algorithm processes them step by step into output data or uses them to determine the solution to the problem.
WHAT IS THE PURPOSE OF A FIELD ROUTE PLANNING ALGORITHM?
In route planning, two typical optimisation questions arise:
The Salesman Problem: (also known as the Traveling Salesman Problem or Traveling Salesperson Problem) - a travelling salesman wants to plan their tour as efficiently as possible, i.e. to visit as many important customers as possible without driving unnecessary distances and wasting time and fuel. This can be applied to salespeople and suppliers as well. So how do you determine an optimised route and tour?
The Backpack Problem: If you pack a backpack, you have to manage the space and think carefully about what you put in it. The same applies, for example, to the loading space of vehicles. But also for the planning of orders that are to be 'packed' into one day. Which field appointments should your service do today and which no longer fit into the working day?
If you only have to schedule a handful of field service resources, then you might manage fairly well manually. However, the more resources and restrictions (e.g. scheduling constraints or vehicle types) you must take into account, the more difficult it becomes to determine the best route and tour planning. This is where algorithms are critical.
ALGORITHMS ACCELERATE AND OPTIMISE FIELD PLANNING
An algorithm for route and tour planning is clearly superior to manual scheduling above a certain complexity. On its basis and with the corresponding computing power, specialist software programmes find the optimal solution not only for the problem of the travelling salesman and for the backpack problem, but also for all other complexities in route and tour planning. And this is infinitely faster than manual planning or scheduling with Excel or Outlook,
Google Maps and Waze.
Read more: Stop planning Field Service Appointments with Outlook
With a specialist route planning algorithm, you achieve better and more efficient results. Software like
FLS VISITOUR makes a large number of complex calculations in a very short time in order to pack your 'backpack' with orders in the best possible way and to determine the most efficient route for your 'travelling salesmen'.
On the one hand, the tour planning software accelerates the processes in scheduling and field service control. On the other hand, the algorithm ensures that the optimal deployment and tour planning is found according to your needs and preset parameters.