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Article: Stochastic programming approach to process flexibility design
Title | Stochastic programming approach to process flexibility design |
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Authors | |
Keywords | Manufacturing systems Stochastic programming Process flexibility Demand uncertainty |
Issue Date | 2009 |
Citation | Flexible Services and Manufacturing Journal, 2009, v. 21, n. 3-4, p. 75-91 How to Cite? |
Abstract | Service and manufacturing firms often attempt to mitigate demand-supply mismatch risks by deploying flexible resources that can be adapted to serve multiple demand classes. It is critical to evaluate the trade-off between the cost of investing in such resources and the resulting benefits. In this paper, we show that the heavily advocated "chaining" heuristic can sometimes perform unsatisfactorily when resources are not perfectly flexible. Alternatively, we propose an integer stochastic programming formulation as an attempt to optimize the flexibility structure. Although it is intractable to compute the optimal solution exactly, we propose a Lagrangian-relaxation heuristic that generates high-quality solutions efficiently. Using computational experiments, we identify conditions under which our approach can outperform the popular chaining solution. |
Persistent Identifier | http://hdl.handle.net/10722/296237 |
ISSN | 2021 Impact Factor: 2.209 2020 SCImago Journal Rankings: 0.934 |
ISI Accession Number ID |
DC Field | Value | Language |
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dc.contributor.author | Mak, Ho Yin | - |
dc.contributor.author | Shen, Zuo Jun Max | - |
dc.date.accessioned | 2021-02-11T04:53:08Z | - |
dc.date.available | 2021-02-11T04:53:08Z | - |
dc.date.issued | 2009 | - |
dc.identifier.citation | Flexible Services and Manufacturing Journal, 2009, v. 21, n. 3-4, p. 75-91 | - |
dc.identifier.issn | 1936-6582 | - |
dc.identifier.uri | http://hdl.handle.net/10722/296237 | - |
dc.description.abstract | Service and manufacturing firms often attempt to mitigate demand-supply mismatch risks by deploying flexible resources that can be adapted to serve multiple demand classes. It is critical to evaluate the trade-off between the cost of investing in such resources and the resulting benefits. In this paper, we show that the heavily advocated "chaining" heuristic can sometimes perform unsatisfactorily when resources are not perfectly flexible. Alternatively, we propose an integer stochastic programming formulation as an attempt to optimize the flexibility structure. Although it is intractable to compute the optimal solution exactly, we propose a Lagrangian-relaxation heuristic that generates high-quality solutions efficiently. Using computational experiments, we identify conditions under which our approach can outperform the popular chaining solution. | - |
dc.language | eng | - |
dc.relation.ispartof | Flexible Services and Manufacturing Journal | - |
dc.rights | This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License. | - |
dc.subject | Manufacturing systems | - |
dc.subject | Stochastic programming | - |
dc.subject | Process flexibility | - |
dc.subject | Demand uncertainty | - |
dc.title | Stochastic programming approach to process flexibility design | - |
dc.type | Article | - |
dc.description.nature | published_or_final_version | - |
dc.identifier.doi | 10.1007/s10696-010-9062-3 | - |
dc.identifier.scopus | eid_2-s2.0-79951856919 | - |
dc.identifier.volume | 21 | - |
dc.identifier.issue | 3-4 | - |
dc.identifier.spage | 75 | - |
dc.identifier.epage | 91 | - |
dc.identifier.eissn | 1936-6590 | - |
dc.identifier.isi | WOS:000283942100001 | - |
dc.identifier.issnl | 1936-6582 | - |