Field service operation is a theoretically complex problem. Numerous tasks at various locations need to be assigned to service staff. Skills, capabilities, and the level of local knowledge have to be considered to estimate the time required to complete a task by a group of selected technicians. Multiple objectives involve cost, task priorities, and consumer satisfaction. The cost includes the salary of service staff for a whole route from departing to returning to the base location. The travel cost depends on the proper routing of the service staff and the effective collection of closely located tasks into a single route. Priorities of tasks are defined by a function of their deadlines. Consumer satisfaction is a function of the number of missed appointments.

A two-level optimization model is introduced to solve large-scale field service operation problems. At the higher level, tasks are assigned to time intervals based on the capacity and availability of the service groups. Then at the lower level, assigned tasks are exactly scheduled and service routes planned by time-constrained process network synthesis (TCPNS). The execution of the different levels is performed iteratively until the overall work plan cannot be further improved.

现场服务操作是一个理论上复杂的问题。需要将不同地点的大量任务分配给服务人员。必须考虑技能、能力和当地知识水平，以估计一组选定的技术人员完成任务所需的时间。多个目标涉及成本、任务优先级和消费者满意度。费用包括从出发到返回基地的整条路线服务人员的工资。差旅成本取决于服务人员的正确路线以及将位置较近的任务有效地收集到单一路线中。任务的优先级由其最后期限的函数定义。消费者满意度是错过预约次数的函数。

引入两级优化模型来解决大规模现场服务运营问题。在更高级别，根据服务组的容量和可用性将任务分配到时间间隔。然后在较低级别，通过时间约束过程网络综合（TCPNS）精确调度分配的任务和规划服务路线。不同层次的执行是迭代执行的，直到整体工作计划无法进一步改进。