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