International Journal of Computational Intelligence Research (IJCIR)

Volume 2, Number 4 (2006)


Heuristic methods for automatic rotating workforce scheduling

Musliu Nysret
Vienna University of Technology Karlsplatz 13, 1040 Wien, Austria


Rotating workforce scheduling appears in different forms in a broad range of workplaces, such as industrial plants, call centers, public transportation, and airline companies. It is of a high practical relevance to find workforce schedules that fulfill the ergonomic criteria of the employees, and reduce costs for the organization.

In this paper we propose new heuristic methods for automatic generation of rotating workforce schedules. To improve the quality of each heuristic method alone, we further propose the hybridization of these methods. The following methods are proposed: (1) A Tabu Search (TS) based algorithm, (2) A heuristic method based on min-conflicts heuristic (MC), (3) A method that includes in the tabu search algorithm the min-conflicts heuristic (TS-MC) and random walk (TS-RW), (4) A method that includes in the min-conflicts heuristic the tabu mechanism (MC-T), random walk (MC-RW), and both the tabu mechanism and the random walk (MC-T-RW). The appropriate neighborhood structure, tabu mechanism, and fitness function, based on the specifics of the problem are proposed. The proposed methods are implemented and experimentally evaluated on the benchmark examples given in the literature and on the real life test problems, which we collected from a broad range of organizations. Empirical results show that the combination of the min-conflicts heuristic with tabu search can be used to solve this problem very effectively. The hybrid methods improve the performance of the commercial system for generation of rotating workforce schedules and are currently in the procees of being included in a commercial package for automatic generation of rotating workforce schedules.

rotating workforce scheduling, heuristic search, min-conflicts heuristic, tabu search, random walk, constraint satisfaction.