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Modeling and solving staff scheduling with partial weighted maxSAT

Employee scheduling is a well known problem that appears in a wide range of different areas including health care, air lines, transportation services, and basically any organization that has to deal with workforces. In this paper we model a collection of challenging staff scheduling instances as a w...

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Detalles Bibliográficos
Autores principales: Demirović, Emir, Musliu, Nysret, Winter, Felix
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer US 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6394591/
https://www.ncbi.nlm.nih.gov/pubmed/30880860
http://dx.doi.org/10.1007/s10479-017-2693-y
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author Demirović, Emir
Musliu, Nysret
Winter, Felix
author_facet Demirović, Emir
Musliu, Nysret
Winter, Felix
author_sort Demirović, Emir
collection PubMed
description Employee scheduling is a well known problem that appears in a wide range of different areas including health care, air lines, transportation services, and basically any organization that has to deal with workforces. In this paper we model a collection of challenging staff scheduling instances as a weighted partial Boolean maximum satisfiability (maxSAT) problem. Using our formulation we conduct a comparison of four different cardinality constraint encodings and analyze their applicability on this problem. Additionally, we measure the performance of two leading solvers from the maxSAT evaluation 2015 in a series of benchmark experiments and compare their results to state of the art solutions. In the process we also generate a number of challenging maxSAT instances that are publicly available and can be used as benchmarks for the development and verification of modern SAT solvers.
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spelling pubmed-63945912019-03-15 Modeling and solving staff scheduling with partial weighted maxSAT Demirović, Emir Musliu, Nysret Winter, Felix Ann Oper Res Patat 2016 Employee scheduling is a well known problem that appears in a wide range of different areas including health care, air lines, transportation services, and basically any organization that has to deal with workforces. In this paper we model a collection of challenging staff scheduling instances as a weighted partial Boolean maximum satisfiability (maxSAT) problem. Using our formulation we conduct a comparison of four different cardinality constraint encodings and analyze their applicability on this problem. Additionally, we measure the performance of two leading solvers from the maxSAT evaluation 2015 in a series of benchmark experiments and compare their results to state of the art solutions. In the process we also generate a number of challenging maxSAT instances that are publicly available and can be used as benchmarks for the development and verification of modern SAT solvers. Springer US 2017-11-07 2019 /pmc/articles/PMC6394591/ /pubmed/30880860 http://dx.doi.org/10.1007/s10479-017-2693-y Text en © The Author(s) 2017 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.
spellingShingle Patat 2016
Demirović, Emir
Musliu, Nysret
Winter, Felix
Modeling and solving staff scheduling with partial weighted maxSAT
title Modeling and solving staff scheduling with partial weighted maxSAT
title_full Modeling and solving staff scheduling with partial weighted maxSAT
title_fullStr Modeling and solving staff scheduling with partial weighted maxSAT
title_full_unstemmed Modeling and solving staff scheduling with partial weighted maxSAT
title_short Modeling and solving staff scheduling with partial weighted maxSAT
title_sort modeling and solving staff scheduling with partial weighted maxsat
topic Patat 2016
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6394591/
https://www.ncbi.nlm.nih.gov/pubmed/30880860
http://dx.doi.org/10.1007/s10479-017-2693-y
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