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Exact and Heuristic Methods for Multi-Activity Tour Scheduling Problems

Abstract : Personnel scheduling problems encompass a large collection of optimization challenges thatseveral organizations need to face. One of the first classifications proposed divides theseproblems into: days-o_ scheduling, shift scheduling, and tour scheduling. The first concernsthe determination of working and rest days; the second defines the shifts to be assigned; thethird integrates days-o_ into shift scheduling. The current thesis addresses the tour scheduling problem with a multi-activity context arising in restaurant business, which was provided by the company Horizontal Software. As such, the main goal is to define the working days and the shifts, along with the specification of the activities in each time period. This problem is also characterized by a high degree of flexibility, mainly due to the introduction of a long pause (interruption), and heterogeneity, determined by conditions from employees (skills, availabilities, contract regulations, and pre-assignments). The problem is tackled by a Branch-and-Price algorithm, which is based on column generation. A dual ascent heuristic is implemented to speed up its convergence, and a constraint and dynamic programming based method is proposed for generating schedules. To address the large-scale instances, various heuristics are presented, based on column generation, large neighborhood search and tabu search. To assess the performance of the proposed method,computational experiments are conducted on instances from the literature and on real-worldinstances that were provided by Horizontal Software.
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Stefania Pan. Exact and Heuristic Methods for Multi-Activity Tour Scheduling Problems. Computers and Society [cs.CY]. Université Sorbonne Paris Cité, 2018. English. ⟨NNT : 2018USPCD080⟩. ⟨tel-02613681⟩

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