<p>The provision of technician-based after-sales field services, such as installing, repairing, or maintaining consumer goods, requires operational planning to schedule and route skilled technicians under various operational constraints and objectives. From a methodological perspective, these operational planning problems belong to the class of Technician Routing and Scheduling Problems (TRSPs). To address the high heterogeneity of the TRSP literature, we conduct a model-based literature review that structures the literature at the modeling level rather than solely at the problem level. The survey is based on a taxonomy, which allows us to represent a static-deterministic TRSP as a specific configuration of core routing constraints, service- and technician-related constraints, and objectives. The taxonomy also covers stochastic-dynamic TRSPs, which are additionally characterized by sequential decision-making and uncertainty, and are becoming increasingly relevant in both research and practice due to the progress in mobile communication technology. Drawing on the taxonomy-based literature classification, we identify real-world TRSP configurations that are underrepresented in the scientific literature. These include, e.g., TRSPs combining teaming with synchronization as well as TRSPs involving demand management decisions by the provider.</p>

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A model-based survey on operational planning of technician-based after-sales field services

  • Elion Shala,
  • David Fleckenstein,
  • Robert Klein

摘要

The provision of technician-based after-sales field services, such as installing, repairing, or maintaining consumer goods, requires operational planning to schedule and route skilled technicians under various operational constraints and objectives. From a methodological perspective, these operational planning problems belong to the class of Technician Routing and Scheduling Problems (TRSPs). To address the high heterogeneity of the TRSP literature, we conduct a model-based literature review that structures the literature at the modeling level rather than solely at the problem level. The survey is based on a taxonomy, which allows us to represent a static-deterministic TRSP as a specific configuration of core routing constraints, service- and technician-related constraints, and objectives. The taxonomy also covers stochastic-dynamic TRSPs, which are additionally characterized by sequential decision-making and uncertainty, and are becoming increasingly relevant in both research and practice due to the progress in mobile communication technology. Drawing on the taxonomy-based literature classification, we identify real-world TRSP configurations that are underrepresented in the scientific literature. These include, e.g., TRSPs combining teaming with synchronization as well as TRSPs involving demand management decisions by the provider.