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Many-Objective Nurse Scheduling using NSGA-II based on Pareto Partial Dominance with Linear Subset-size Scheduling

Topics: Applications: Games and Entertainment Technologies, Evolutionary Robotics, Evolutionary Art and Design, Industrial and Real World applications, Computational Economics and Finance; Evolutionary Multi-objective Optimization; Evolvable Computing; Genetic Algorithms

Author: Makoto Ohki

Affiliation: Department of Information and Electronics, Graduate School of Tottori University, 4, 101 Koyama-Minami, Tottori and Tottori 680-8552 Japan

ISBN: 978-989-758-327-8

Keyword(s): Many-objective Optimization, Combinatorial Optimization, Nurse Scheduling, Evolutionary Algorithm, NSGA-II, Pareto Partial Dominance, Sub-set Size Scheduling.

Abstract: This paper describes a nurse scheduling in Japanese standard general hospitals. In the standard general hospital in Japan basically three shift system is adopted for nurses working in there. We have compiled evaluations of the monthly nurse schedule into twelve penalty functions in the past work. These twelve penalty functions are translated to twelve objective functions in this paper. The nurse scheduling with twelve objective functions is solved as a multi-objective optimization problem by means of NSGA-II. The optimization is insufficient when NSGA-II is applied to such an optimization problem with four or more objective functions, known as a many-objective optimization problem. One method for reducing this problem is a technique based on Pareto partial dominance. In this technique, the partial non-dominated sorting is executed by using a subset selected from all objective functions. In the conventional technique, the schedule of subset size over optimization has to be prepared bef orehand in the form of a list. Moreover, the selection list brings a great influence on the result of optimization. Creating such a selection list is a heavy burden for the user. This paper proposes a technique of NSGA-II based on Pareto partial dominance with a linear subset-size scheduling. By embedding the subset-size scheduling into the algorithm, the user, namely the chief nurse, is released from the designing of the selection list. (More)

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Paper citation in several formats:
Ohki, M. (2018). Many-Objective Nurse Scheduling using NSGA-II based on Pareto Partial Dominance with Linear Subset-size Scheduling.In Proceedings of the 10th International Joint Conference on Computational Intelligence - Volume 1: IJCCI, ISBN 978-989-758-327-8, pages 118-125. DOI: 10.5220/0006894501180125

@conference{ijcci18,
author={Makoto Ohki.},
title={Many-Objective Nurse Scheduling using NSGA-II based on Pareto Partial Dominance with Linear Subset-size Scheduling},
booktitle={Proceedings of the 10th International Joint Conference on Computational Intelligence - Volume 1: IJCCI,},
year={2018},
pages={118-125},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006894501180125},
isbn={978-989-758-327-8},
}

TY - CONF

JO - Proceedings of the 10th International Joint Conference on Computational Intelligence - Volume 1: IJCCI,
TI - Many-Objective Nurse Scheduling using NSGA-II based on Pareto Partial Dominance with Linear Subset-size Scheduling
SN - 978-989-758-327-8
AU - Ohki, M.
PY - 2018
SP - 118
EP - 125
DO - 10.5220/0006894501180125

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