An integrated solution approach for multi-objective, multi-skill workforce scheduling and routing problems

We study the multi-skill workforce scheduling and routing problem in field service operations. It is motivated by a real-life problem faced by electricity distribution companies on a daily basis. Given a set of technicians with different skills and a set of geographically dispersed tasks with different skill requirements and priorities, the aim is to form teams of technicians and to assign a sequence of tasks to each team according to their skills. There are two objectives: completing higher priority tasks earlier and minimizing total operational costs. We propose a mixed integer programming model to find Pareto optimal solutions. Because the computational effort considerably increases for real life problem instances, we propose a two-stage matheuristic to obtain a good approximation of the Pareto frontier. We demonstrate the performance of the proposed matheuristic in real life problem instances and instances from the literature. (C) 2020 Elsevier Ltd. All rights reserved.