Computational Study for the Workforce Scheduling and Routing Problem

In this paper we present a computational study on 112 instances of the workforce scheduling and routing problem (WSRP). This problem has applications in many service provider industries where employees are required to visit customers to perform certain activities. Given their similarity, we adapt a mathematical programming model from the literature on vehicle routing problem with time windows (VRPTW) to conduct this computational study on the WSRP. We also generate a set of WSRP instances from a well-known VRPTW data set. This work has three objectives. First, to investigate feasibility and optimality on a range of medium size WSRP instances with different distribution of visiting locations and including teaming and connected activities constraints. Second, to compare the generated WSRP instances to their counterpart VRPTW instances with respect to their difficulty. Third, to determine the computation time required by a current mathematical programming solver to find feasible solutions for the generated WSRP instances. This helps us to better assess the difficulty of the WSRP problem to inform the development of other solution approaches in the future. It is observed that although the solver can achieve feasible solutions for some instances, the current solver capabilities are still limited, hence other solutions methods must be considered. Another observation is that the WSRP instances present an increased degree of difficulty because of the additional constraints. The key contribution of this paper is to present some test instances and corresponding benchmark study for the workforce scheduling and routing problem.