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Optimization Models for Scheduling of Jobs

This work is motivated by a particular scheduling problem that is faced by logistics centers that perform aircraft maintenance and modification. Here we concentrate on a single facility (hangar) which is equipped with several work stations (bays). Specifically, a number of jobs have already been sch...

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Detalles Bibliográficos
Autores principales: Indika, S. H. Sathish, Shier, Douglas R.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: [Gaithersburg, MD] : U.S. Dept. of Commerce, National Institute of Standards and Technology 2006
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4662499/
https://www.ncbi.nlm.nih.gov/pubmed/27274921
http://dx.doi.org/10.6028/jres.111.009
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author Indika, S. H. Sathish
Shier, Douglas R.
author_facet Indika, S. H. Sathish
Shier, Douglas R.
author_sort Indika, S. H. Sathish
collection PubMed
description This work is motivated by a particular scheduling problem that is faced by logistics centers that perform aircraft maintenance and modification. Here we concentrate on a single facility (hangar) which is equipped with several work stations (bays). Specifically, a number of jobs have already been scheduled for processing at the facility; the starting times, durations, and work station assignments for these jobs are assumed to be known. We are interested in how best to schedule a number of new jobs that the facility will be processing in the near future. We first develop a mixed integer quadratic programming model (MIQP) for this problem. Since the exact solution of this MIQP formulation is time consuming, we develop a heuristic procedure, based on existing bin packing techniques. This heuristic is further enhanced by application of certain local optimality conditions.
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spelling pubmed-46624992016-06-03 Optimization Models for Scheduling of Jobs Indika, S. H. Sathish Shier, Douglas R. J Res Natl Inst Stand Technol Article This work is motivated by a particular scheduling problem that is faced by logistics centers that perform aircraft maintenance and modification. Here we concentrate on a single facility (hangar) which is equipped with several work stations (bays). Specifically, a number of jobs have already been scheduled for processing at the facility; the starting times, durations, and work station assignments for these jobs are assumed to be known. We are interested in how best to schedule a number of new jobs that the facility will be processing in the near future. We first develop a mixed integer quadratic programming model (MIQP) for this problem. Since the exact solution of this MIQP formulation is time consuming, we develop a heuristic procedure, based on existing bin packing techniques. This heuristic is further enhanced by application of certain local optimality conditions. [Gaithersburg, MD] : U.S. Dept. of Commerce, National Institute of Standards and Technology 2006 2006-04-01 /pmc/articles/PMC4662499/ /pubmed/27274921 http://dx.doi.org/10.6028/jres.111.009 Text en https://creativecommons.org/publicdomain/zero/1.0/ The Journal of Research of the National Institute of Standards and Technology is a publication of the U.S. Government. The papers are in the public domain and are not subject to copyright in the United States. Articles from J Res may contain photographs or illustrations copyrighted by other commercial organizations or individuals that may not be used without obtaining prior approval from the holder of the copyright.
spellingShingle Article
Indika, S. H. Sathish
Shier, Douglas R.
Optimization Models for Scheduling of Jobs
title Optimization Models for Scheduling of Jobs
title_full Optimization Models for Scheduling of Jobs
title_fullStr Optimization Models for Scheduling of Jobs
title_full_unstemmed Optimization Models for Scheduling of Jobs
title_short Optimization Models for Scheduling of Jobs
title_sort optimization models for scheduling of jobs
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4662499/
https://www.ncbi.nlm.nih.gov/pubmed/27274921
http://dx.doi.org/10.6028/jres.111.009
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