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An Iterated Local Search Heuristic for the Staff Scheduling Problem for Part-Time Employees in Japan

In this paper, we introduce a mathematical programming model for solving a staff scheduling problem based on one-day duties (task patterns) of individual staff members. The model can accommodate various service types, management policies, and staff preferences. We first enumerate all feasible one-da...

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Published in:	Asia-Pacific journal of operational research 2022-10, Vol.39 (5)
Main Authors:	Wu, Wei, Katoh, Naoaki, Ikegami, Atsuko
Format:	Article
Language:	English
Subjects:	Algorithms Dynamic programming Mathematical programming Operations research Part time employment Scheduling Searching Task scheduling
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description	In this paper, we introduce a mathematical programming model for solving a staff scheduling problem based on one-day duties (task patterns) of individual staff members. The model can accommodate various service types, management policies, and staff preferences. We first enumerate all feasible one-day duties and propose an iterated local search approach that incorporates various methodologies, including a size-reduction method and a very large-scale neighborhood search. For the very large-scale neighborhood search, we design a dynamic programming method that aims to find the most improved schedule and can be used in the rescheduling stage. Computational results show that the model and the proposed algorithm perform well for real-world instances in Japan.
doi_str_mv	10.1142/S0217595921500378
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subjects	Algorithms Dynamic programming Mathematical programming Operations research Part time employment Scheduling Searching Task scheduling
title	An Iterated Local Search Heuristic for the Staff Scheduling Problem for Part-Time Employees in Japan
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