Solving technician routing and scheduling problem using improved particle swarm optimization

In this paper, an improved particle swarm optimization (IPSO) algorithm is proposed to solve the technician routing and scheduling problem (TRSP). The TRSP consists of the assignment of technicians into teams, the assignment of teams to tasks, the construction of routes, and the selection of the day on which a service is provided by considering the proficiency level of workers and the proficiency requirement of the task. The paper considers the planning horizon as a multi-period covering 5 days, which further increases the complexity of the problem. Then a task can be fulfilled in any one of 5 days. The IPSO algorithm includes a particle swarm optimization (PSO) algorithm and one neighborhood operator. One neighborhood operator is used to avoid the local solution trap since the global best solution found by PSO is falling into a local solution trap. Further, the proposed algorithm's performance is experimentally compared with the branch-and-cut algorithm for the solution of the TRSP, on the benchmark instances generated from the literature. The computational results show that IPSO provides better solutions considering the branch-and-cut algorithm within reasonable computing time.