A Fast Reoptimization Approach for the Dynamic Technician Routing and Scheduling Problem

The Technician Routing and Scheduling Problem Technician Routing and Scheduling Problem (TRSP) consists in routing staff to serve requests for service, taking into account Time windows time windows, Skills skills, tools, and Spare parts spare parts. Typical applications include maintenance operations and staff routing in telecoms, public utilities, and in the health care industry. In this paper we tackle the Dynamic TRSP Dynamic TRSP (D-TRSP) in which new requests appear over time. We propose a fast reoptimization approach based on a parallel Large Neighborhood Search Adaptive Large Neighborhood Search (RpALNS) able to achieve state-of-the-art results on the Dynamic Vehicle Routing Problem with Time Windows. In addition, we solve a set of randomly generated D-TRSP instances and discuss the potential gains with respect to a heuristic modeling a human dispatcher solution.