In addition to manual planning via drag-and-drop, dispatchers can also use the automatic scheduling in mobileX-Dispatch, the Optimizer, when planning the assignments of their technicians. The fully automatic planning distributes all orders and operations to the available resources - without exceptions and restrictions by the dispatcher. In semi-automatic planning, the dispatcher first determines a specific time period for the optimization. This can be a long period of several weeks and months or just a certain day. He then defines which types of orders or operations, which locations or resource groups are to be planned or excluded from automatic planning.
The challenge of optimal route planning
The planning of optimal tours becomes all the more demanding the more technicians and assignments have to be planned and the more general conditions and planning goals have to be taken into account. Therefore, the assignment of orders to technicians requires a lot of computing time in theory. In computer science this is called MDVRPTW (Multi Depot Vehicle Routing Problem with Time Windows). This is an NP-complete problem, i.e. a difficult problem that cannot be solved efficiently with the help of today's computers.
Since the available planning time in daily use is limited and not all possible combinations of operations can be calculated, the Optimizer uses certain assumptions (heuristics) to generate sufficiently good tours. Such heuristic methods are based on experience and can lead to practicable solutions with limited knowledge and in a short time. These are then further optimized with regard to the cost function.
Cost function and parameterization
In every possible planning scenario, the cost function defines the costs with regard to certain parameters. These are factors that play an important role in planning for a company. These vary from company to company and depend on the individual business, service and planning strategy. The factors of parameterization, i.e. optimization with regard to cost and benefit target values, include, for example:
- Plannable time of the technician
- Location of the technician
- Skills / qualifications of the technician
- Loading capacities of vehicles
- Service level agreements
- Agreed times
- Estimated duration of operations
The optimizer thus helps to approach an optimum in the distribution of operations. The company describes what the optimum is by assigning certain costs to the individual factors. These can be for example:
- Every minute a technician drives costs 3.50 euros.
- Each operation that cannot be planned costs 100 euros.
- If the preferred technician cannot be planned, this is a loss of quality for the customer. This is valued at 50 euros per operation.
- If an operation cannot be planned in the SLA times, then each hour beyond costs 20 Euro.
Goals of automatic planning
The more complex the target(s) of resource planning are, the more cost parameters influence its achievement. Since these parameters can also be contradictory (shortest versus fastest route), they must be prioritized accordingly and weighted accordingly in the Optimizer interface. Possible goals of the optimized planning can be:
- Shorter journey times -> optimisation to the fastest route
- Less CO2 pollution -> optimisation to the shortest possible route
- Lower costs -> optimization to the shortest and fastest route, high first-time-fix-rate
- High customer satisfaction -> optimization to short time windows, desired appointments, fast appointments, preferred technicians, high first-time-fix-rate
- Optimal resource utilization -> optimization for low overtime, short travel times, high first-time-fix-rate, skill matching
Map integration and calculation of optimal routes
FThe Optimizer uses PTV's digital road map to calculate the tours. Using the geocoordinates of the starting point and the destinations, the PTV server calculates the distances and thus the travel times for all possible routes. From this, the Optimizer calculates the best possible routes according to the cost functions. The calculation includes speed profiles of resources that are stored for certain vehicles. Historical traffic data with time-of-day-dependent or seasonal profiles for routes - such as rush hour - can also be taken into account. The transported goods can also play a role in route planning. If, for example, it is a dangerous goods transport, it may only drive on certain roads.