Iterated local search for workforce scheduling and routing problems

Abstract

The integration of scheduling workers to perform tasks with the traditional vehicle routing problem gives rise to the workforce scheduling and routing problems (WSRP). In the WSRP, a number of service technicians with different skills, and tasks at different locations with pre-defined time windows and skill requirements are given. It is required to find an assignment and ordering of technicians to tasks, where each task is performed within its time window by a technician with the required skill, for which the total cost of the routing is minimized. This paper describes an iterated local search (ILS) algorithm for the WSRP. The performance of the proposed algorithm is evaluated on benchmark instances against an off-the-shelf optimizer and an existing adaptive large neighbourhood search algorithm. The proposed ILS algorithm is also applied to solve the skill vehicle routing problem, which can be viewed as a special case of the WSRP. The computational results indicate that the proposed algorithm can produce high-quality solutions in short computation times.

A concise guide to existing and emerging vehicle routing problem variants

“…Finally, maintenance or home care services may require specific skills. These requirements must be taken into account when assigning technicians and vehicles to tasks (Cappanera et al 2013, Paraskevopoulos et al 2017, Xie et al 2017. In complex situations, several vehicles and workers with different skills and equipment (Eveborn et al 2009, Parragh and) may be jointly requested for a single task, leading to VRPs with synchronization constraints; these are notoriously difficult to solve (Drexl 2012).…”

Exact and hyper‐heuristic solutions for the distribution‐installation problem from the VeRoLog 2019 challenge

“…The study dealt with the availability of tools and spare parts for the technicians and routing them to the depot for the replenishment of tools. Xie et al [67] used an iterated local search algorithm to solve the TRSP. They studied a variant where it was given which technicians can serve which orders.…”

A bi-objective approach based on fuzzy logic for multi-period technician routing and scheduling problems

“…The solution models can be categorized as exact methods ( Mathlouthi et al, 2021b), heuristic models (Graf, 2022), metaheuristic methods ( Pekel, 2022), and hybrid models (Xie et al, 2017). The authors propose the multi-period TRSP considered as a MIP model (Zamorano and Stolletz, 2017).…”