Optimal priority ordering in PHP production of multiple part-types in a failure-prone machine

This note deals with the problem of minimising the expected sum of quadratic holding and shortage inventory costs when a single, failure-prone machine produces multiple part-types. Shu and Perkins (2001) introduce the problem and, by restricting the set of control policies to the class of prioritise...

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Main Authors: Ana Sánchez, Albert Corominas, Rafael Pastor
Format: Article
Language:English
Published: OmniaScience 2009-12-01
Series:Journal of Industrial Engineering and Management
Subjects:
Online Access:http://www.jiem.org/index.php/jiem/article/view/67
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spelling doaj-6d7cba1d7e854fdba2fe2d7b1f8401402020-11-25T00:37:43ZengOmniaScienceJournal of Industrial Engineering and Management2013-84232013-09532009-12-012341843610.3926/jiem..v2n3.p418-43636Optimal priority ordering in PHP production of multiple part-types in a failure-prone machineAna Sánchez0Albert Corominas1Rafael Pastor2Technical University of CataloniaTechnical University of CataloniaTechnical University of CataloniaThis note deals with the problem of minimising the expected sum of quadratic holding and shortage inventory costs when a single, failure-prone machine produces multiple part-types. Shu and Perkins (2001) introduce the problem and, by restricting the set of control policies to the class of prioritised hedging point (PHP) policies, establish simple, analytical expressions for the optimal hedging points provided that the priority ordering of the part-types is given. However, the determination of an optimal priority ordering is left by the authors as an open question. This leaves an embedded sequencing problem which we focus on in this note. We define a lower bound for the problem, introduce a test bed for future developments, and propose three dynamic programming approaches (with or without the lower bound) for determining the optimal priority orderings for the instances of the test bed. This is an initial step in a research project aimed at solving the optimal priority ordering problem, which will allow evaluating the performance of future heuristic and metaheuristic procedures.http://www.jiem.org/index.php/jiem/article/view/67scheduling, cumulative resources, failure-prone machines, prioritised hedging point control, production control
collection DOAJ
language English
format Article
sources DOAJ
author Ana Sánchez
Albert Corominas
Rafael Pastor
spellingShingle Ana Sánchez
Albert Corominas
Rafael Pastor
Optimal priority ordering in PHP production of multiple part-types in a failure-prone machine
Journal of Industrial Engineering and Management
scheduling, cumulative resources, failure-prone machines, prioritised hedging point control, production control
author_facet Ana Sánchez
Albert Corominas
Rafael Pastor
author_sort Ana Sánchez
title Optimal priority ordering in PHP production of multiple part-types in a failure-prone machine
title_short Optimal priority ordering in PHP production of multiple part-types in a failure-prone machine
title_full Optimal priority ordering in PHP production of multiple part-types in a failure-prone machine
title_fullStr Optimal priority ordering in PHP production of multiple part-types in a failure-prone machine
title_full_unstemmed Optimal priority ordering in PHP production of multiple part-types in a failure-prone machine
title_sort optimal priority ordering in php production of multiple part-types in a failure-prone machine
publisher OmniaScience
series Journal of Industrial Engineering and Management
issn 2013-8423
2013-0953
publishDate 2009-12-01
description This note deals with the problem of minimising the expected sum of quadratic holding and shortage inventory costs when a single, failure-prone machine produces multiple part-types. Shu and Perkins (2001) introduce the problem and, by restricting the set of control policies to the class of prioritised hedging point (PHP) policies, establish simple, analytical expressions for the optimal hedging points provided that the priority ordering of the part-types is given. However, the determination of an optimal priority ordering is left by the authors as an open question. This leaves an embedded sequencing problem which we focus on in this note. We define a lower bound for the problem, introduce a test bed for future developments, and propose three dynamic programming approaches (with or without the lower bound) for determining the optimal priority orderings for the instances of the test bed. This is an initial step in a research project aimed at solving the optimal priority ordering problem, which will allow evaluating the performance of future heuristic and metaheuristic procedures.
topic scheduling, cumulative resources, failure-prone machines, prioritised hedging point control, production control
url http://www.jiem.org/index.php/jiem/article/view/67
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AT rafaelpastor optimalpriorityorderinginphpproductionofmultipleparttypesinafailurepronemachine
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