Integrated solution approaches for team forming, scheduling and routing problem for multi-skill tasks with prioritie

In this study, we study the multi-skill workforce scheduling and routing problem that arises in field service operations. It is motivated by a real-life problem that electricity distribution companies face on a daily basis. Given a set of technicians having different skills and a set of geographically dispersed tasks with different skill requirements and priorities, the goal is to form teams of technicians and to assign a sequence of tasks to each team in accordance with their skill requirements. There are two objectives: completing higher priority tasks earlier and minimizing total operational (travelling costs and outsourcing costs) costs. We propose a mixed integer programming (MIP) model to find Pareto optimal solutions. As the computational effort grows drastically for realistic problem instances, we propose a two-stage matheuristic to obtain a good approximation of the Pareto frontier. In first stage, an initial solution is constructed. Then in second stage, solution set from initial solution is composed by using multi objective variable neighborhood search. We demonstrate the performance of the proposed matheuristic through realistic problem instances and instances from the literature.