Solving technician routing and scheduling problem using improved particle swarm optimization
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METHODOLOGIES AND APPLICATION
Solving technician routing and scheduling problem using improved particle swarm optimization Engin Pekel1
Ó Springer-Verlag GmbH Germany, part of Springer Nature 2020
Abstract 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. Keywords Neighborhood operator Particle swarm optimization Technician routing and scheduling
1 Introduction The technician scheduling problems are significant as a way for industries to maintain market share and ensure repeat business (Haugen and Hill 1999). In a competitive market, specialist organizations compete for not only the product they provide but also the quality of client service supplied by them and the after-care service (Khalfay et al. 2017). Many researchers have investigated personnel scheduling due to its presence in many fields (Xu and Chiu 2001; Ernst et al. 2004; Brucker et al. 2011; Krishnamoorthy et al. 2012; Van den Bergh et al. 2013). Several technicians must provide a specified proficiency to carry out various tasks at minimum cost while meeting resource constraints in the technician routing and scheduling problem (TRSP).
Communicated by V. Loia. & Engin Pekel [email protected]; [email protected] 1
Faculty of Engineering, Department of Industrial Engineering, Hitit University, C¸orum, Turkey
The TRSP relates to the type of vehicle routing problems (VRP) with time windows (Golden et al. 2002; Kallehauge et al. 2005; Moradi 2019; Wu et al. 2020). It also includes additional decisions that require to be considered, e.g., 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 (Zamorano and Stolletz 2017). The complexity of routing is an important part of many technician scheduling problems. Regularly, each set of clients exist in their location, a
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