Furthermore, an interface manages the communication between these two components and allows a feedback loop between the simulator and the optimizer to achieve more robust plans. The study uses AnyLogic as field service scheduling software to evaluate the applicability of such plans by taking into account the stochastic factors. The proposed framework relies on an optimization engine for the generation of the daily plans. This work provides a simulation-based field service scheduling solution for supporting decision makers in tackling this challenging problem. A common challenge is to evaluate different design choices, related to staffing decisions, technician scheduling strategies, and technological improvements in order to make the system more efficient. Many companies that deliver units to customer premises need to provide periodical maintenance and services on request by their field service technicians.
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