The solve feature of our API assigns operations at pre-determined locations to various routes by establishing the most cost-effective order in which to perform them. Plan is a new, complementary feature designed to provide users with information invaluable in making adjustments to their scheduling.
Information for Decision Making
In responding to unspecified needs or contingencies, schedulers can marginally adjust optimal route schedules in the field. They make their adjustments through their expertise in balancing the cost and quality of service with various scheduling constraints, most notably time constraints.
The new plan feature allows users to update the ETA of any route while taking into account operational costs and the impact of any changes. For every change, it provides users with pertinent information: the number of delayed jobs, the length of delays, the degree to which time constraints and the theoretical load capacities of vehicles have been exceeded, differences in cost, etc. By providing users with specific information, plan allows them to apply their expertise more proficiently.
A Problem that Appears Simple… on the Surface
When a schedule is overbooked, it is impossible to respect all the time constraints. Is the best solution to leave at the originally scheduled time and be late for certain jobs? If so, our API can determine the length of delays. But it can also propose an earlier starting time, in so far as constraints in the field allow, and thereby reduce delays and lessen the perceived decline in the quality of service.
Or consider the example of a scheduler who wants to move a task originally planned for the afternoon to the very first one on the route. Doing so would change the service time of every subsequent job. In such a case, our API recognizes that the time of this task alone should be altered and proposes moving the starting time up early enough to avoid delays further down the line.
Optimization under the Hood
By making the usual time constraints flexible, the plan feature allows for scheduling changes while minimizing their impact, which is its principal optimization objective. And it also keeps makespans to a minimum while scheduling tasks as early as possible.
The linear programming approach that we have implemented not only guarantees optimal solutions, but it avoids the frequent pitfalls of unreasonably long calculation times. With our cutting-edge ad-hoc modelization, the response-time of our API is so fast that users can take advantage of it in real time.
Contact us to learn more about what this new feature might mean for you.