How to prevent schedules from slipping?

    Having optimized your routes, you notice that some of your visits are recorded as being late in the Status column following optimization (that is, they appear outside the configured visit time windows).

    Two constraints are available to help avoid late service delivery:

    • End visit before closing time
    • Lateness tolerance

    End visit before closing time

    This constraint allows you to indicate whether the visit can finish after the customer’s Closing time.
    To limit the possibility of potential lateness, use the constraint End visit before closing time set to a value of 1.
    In this case, the resource should take the Visit duration into account to ensure they leave before the configured Closing time.


    A 20-minute delivery must be made at a customer with opening hours of 9.00am-12.00 midday.

    Constraints to use:
    Visit duration = 00:20:00
    Opening time = 09:00:00
    Closing time = 12:00:00
    End visit before closing time = 1

    The resource should arrive at the customer’s at the latest at 11:40:00, stay for 20 minutes, and then leave.

    Lateness tolerance

    The Lateness tolerance constraint allows you to define a late delivery tolerance threshold by entering a value between 0 and 5.

    A value for punctuality of 1 allows greater flexibility than a punctuality value of 5. Customers having a punctuality value of 5 will be less at risk of being visited late than customers with a punctuality value of 2. A punctuality where the acceptability of being late is null (=5) will impose limitations on the optimization and make avoiding late arrival the main priority. So this means it is best not to assign a value of 5 to all customers.

    Example 1:

    You can qualify your VIP customers by entering a value of 5 under Lateness tolerance and isolate other customers for whom a late arrival is of little consequence by entering a value of 2 under Lateness tolerance.

    Example 2:

    You can manage the geographic distances involved by entering a value of 5 under Lateness tolerance for customers that are located a long way from the resources involved, and a value of 2 for other customers: TourSolver will arrange the far away visits first, so late arrival times are more controllable, and visits to closer customers on the return journey. 

    Example 3:

    You can enter a value of 5 under Lateness tolerance for customers with opening hours that are relatively constrained (eg Visit duration = 30m. Opening time = 9.00-10.00am) and a value of 2 for other customers. 

     Note that by default TourSolver will calculate to avoid late incidents as far as possible. It is therefore fruitless to adjust all the constraints at once: it is better to assess the risk you want to take of the schedule slipping, and then adjust constraints one by one to see what effect this has on the optimization result. Take care also to check the precision of the values entered under the Opening time and Closing time customer constraints.


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