Iterated local search for workforce scheduling and routing problems

Fulin Xie (), Chris N. Potts () and Tolga Bektaş ()
Additional contact information
Fulin Xie: CORMSIS, University of Southampton
Chris N. Potts: CORMSIS, University of Southampton
Tolga Bektaş: University of Southampton

Journal of Heuristics, 2017, vol. 23, issue 6, No 3, 500 pages

Abstract: 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.

Keywords: Workforce scheduling; Vehicle routing; Iterated local search (search for similar items in EconPapers)
Date: 2017
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Citations: View citations in EconPapers (4)

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DOI: 10.1007/s10732-017-9347-8

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