Optimization for the Midwest territory is set to automatically run each night for the next...

The requirement is best implemented with High optimization runtime when priorities are similar and candidate counts are large. A longer runtime gives the optimizer more time to evaluate combinations. When many appointments have the same priority and each appointment has many qualifying resources, the search space expands and a higher runtime can improve schedule quality.

Salesforce Field Service treats the Service Appointment as the primary unit of scheduling. Scheduling Policies combine Work Rules, which determine whether a resource or time slot is valid, with Service Objectives, which score valid alternatives against business priorities. The selected configuration therefore has to operate at the scheduling layer rather than merely changing descriptive fields on the parent Work Order.

The alternatives address different parts of the Field Service model. A blank Scheduling Policy is a configuration issue rather than a reason to spend more optimization time, and disabling travel/break calculations changes the model rather than increasing optimization complexity in the way described.

This approach keeps the implementation aligned with the standard Field Service data model and avoids unnecessary customization. Study Guide reference: Managing Scheduling and Optimization — Optimization runtime; candidate volume; appointment priority.