Coredinat Factory and Route Optimization

Route optimization is an important process for many businesses that operate a fleet of vehicles. It helps reduce transportation costs and increase efficiency by optimizing the routes used by drivers. One way to further optimize routing is to consider the different types of customers served.

COREDINAT Factory is a software + hardware solution designed taking into account the requirements of industrial customers. Routing optimization has been further developed by taking into account the needs of factory customers.

Personnel services management in factories requires a chaotic work in order not to disrupt production processes and is highly dependent on human resources. This dependency requires bus drivers to know the stops.

Geographic information systems (GIS) and artificial intelligence are used to optimize routing for staff's homes or fixed stops, and to map staff locations and the best routes to follow. AI can also take into account variables such as traffic congestion, weather conditions and road closures.

Using COREDINAT factory, businesses can create separate routing plans for each service type, taking into account the specific needs and requirements of each group. This increases efficiency and reduces service costs by 35% by minimizing travel time, reducing fuel consumption and improving delivery accuracy.

Another way to optimize routing based on varying address and staffing types is to use machine learning algorithms that can analyze data on customer behavior and preferences. This data is used to predict future delivery patterns and optimize routing plans accordingly. COREDINAT Factory has structured its algorithms flexibly and trained artificial intelligence according to the customer's personnel recruitment pattern (fixed stops or home pick-up).

As a result, the efficiency and effectiveness of service operations increases according to variable customer types. Using machine learning algorithms, COREDINAT Factory can create custom routing plans for each type of customer, taking into account their unique needs and preferences. Thus, the workload of personnel responsible for service operations, such as the chief driver and human resources, is lightened. With fewer vehicles and fewer drivers, there is a decrease in overtime costs.