Loading…
Multiobjective supply chain design under uncertainty
In this article, the design and retrofit problem of a supply chain (SC) consisting of several production plants, warehouses and markets, and the associated distribution systems, is considered. The first problem formulation modifies and extends other previously presented models, in order to include s...
Saved in:
Published in: | Chemical engineering science 2005-03, Vol.60 (6), p.1535-1553 |
---|---|
Main Authors: | , , , , |
Format: | Article |
Language: | English |
Subjects: | |
Citations: | Items that this one cites Items that cite this one |
Online Access: | Get full text |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
cited_by | cdi_FETCH-LOGICAL-c358t-212078a17589605313eb3bf5314611efe7e5053af38a14eb3abcc81a40b4c6a33 |
---|---|
cites | cdi_FETCH-LOGICAL-c358t-212078a17589605313eb3bf5314611efe7e5053af38a14eb3abcc81a40b4c6a33 |
container_end_page | 1553 |
container_issue | 6 |
container_start_page | 1535 |
container_title | Chemical engineering science |
container_volume | 60 |
creator | Guillén, G. Mele, F.D. Bagajewicz, M.J. Espuña, A. Puigjaner, L. |
description | In this article, the design and retrofit problem of a supply chain (SC) consisting of several production plants, warehouses and markets, and the associated distribution systems, is considered. The first problem formulation modifies and extends other previously presented models, in order to include several essential characteristics for realistically representing the consequences of design decisions on the SC performance. Then, in order to take into account the effects of the uncertainty in the production scenario, a two-stage stochastic model is constructed. The problem objective, i.e., SC performance, is assessed by taking into account not only the profit over the time horizon, but also the resulting demand satisfaction. This approach can be used to obtain different kinds of solutions, that may be valuable at different levels. On one hand, the SC configurations obtained by means of deterministic mathematical programming can be compared with those determined by different stochastic scenarios representing different approaches to face uncertainty. Additionally, this approach enables to consider and manage the financial risk associated to the different design options, resulting in a set of Pareto optimal solutions that can be used for decision-making. |
doi_str_mv | 10.1016/j.ces.2004.10.023 |
format | article |
fullrecord | <record><control><sourceid>proquest_cross</sourceid><recordid>TN_cdi_proquest_miscellaneous_28547026</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><els_id>S0009250904008449</els_id><sourcerecordid>28547026</sourcerecordid><originalsourceid>FETCH-LOGICAL-c358t-212078a17589605313eb3bf5314611efe7e5053af38a14eb3abcc81a40b4c6a33</originalsourceid><addsrcrecordid>eNp9kD1PwzAQhi0EEqXwA9iywJZwju04FROq-JKKWGC2HOcCjtKk2Eml_nuuaiU2Fp_v9Xsffhi75pBx4MVdmzmMWQ4gKc8gFydsxkstUilBnbIZACzSXMHinF3E2FKqNYcZk29TN_qhatGNfotJnDabbpe4b-v7pMbov_pk6msMdDoMI8nj7pKdNbaLeHWMc_b59PixfElX78-vy4dV6oQqxzTnOejScq3KRQFKcIGVqBq6yIJzbFCjItk2gkyS3mzlXMmthEq6wgoxZ7eHvpsw_EwYR7P20WHX2R6HKZq8VFJDXpCRH4wuDDEGbMwm-LUNO8PB7PmY1hAfs-ezl4gP1dwcm9vobNcE2zsf_woLJaSmnefs_uBD-unWYzDReSQYtQ8EzdSD_2fKL3gAedA</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>28547026</pqid></control><display><type>article</type><title>Multiobjective supply chain design under uncertainty</title><source>ScienceDirect Journals</source><creator>Guillén, G. ; Mele, F.D. ; Bagajewicz, M.J. ; Espuña, A. ; Puigjaner, L.</creator><creatorcontrib>Guillén, G. ; Mele, F.D. ; Bagajewicz, M.J. ; Espuña, A. ; Puigjaner, L.</creatorcontrib><description>In this article, the design and retrofit problem of a supply chain (SC) consisting of several production plants, warehouses and markets, and the associated distribution systems, is considered. The first problem formulation modifies and extends other previously presented models, in order to include several essential characteristics for realistically representing the consequences of design decisions on the SC performance. Then, in order to take into account the effects of the uncertainty in the production scenario, a two-stage stochastic model is constructed. The problem objective, i.e., SC performance, is assessed by taking into account not only the profit over the time horizon, but also the resulting demand satisfaction. This approach can be used to obtain different kinds of solutions, that may be valuable at different levels. On one hand, the SC configurations obtained by means of deterministic mathematical programming can be compared with those determined by different stochastic scenarios representing different approaches to face uncertainty. Additionally, this approach enables to consider and manage the financial risk associated to the different design options, resulting in a set of Pareto optimal solutions that can be used for decision-making.</description><identifier>ISSN: 0009-2509</identifier><identifier>EISSN: 1873-4405</identifier><identifier>DOI: 10.1016/j.ces.2004.10.023</identifier><identifier>CODEN: CESCAC</identifier><language>eng</language><publisher>Oxford: Elsevier Ltd</publisher><subject>Applications of mathematics to chemical engineering. Modeling. Simulation. Optimization ; Applied sciences ; Chemical engineering ; Economics. Management. Design assessment ; Exact sciences and technology ; Optimisation ; Risk management ; Safety ; Supply chain management</subject><ispartof>Chemical engineering science, 2005-03, Vol.60 (6), p.1535-1553</ispartof><rights>2004 Elsevier Ltd</rights><rights>2005 INIST-CNRS</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c358t-212078a17589605313eb3bf5314611efe7e5053af38a14eb3abcc81a40b4c6a33</citedby><cites>FETCH-LOGICAL-c358t-212078a17589605313eb3bf5314611efe7e5053af38a14eb3abcc81a40b4c6a33</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,780,784,27924,27925</link.rule.ids><backlink>$$Uhttp://pascal-francis.inist.fr/vibad/index.php?action=getRecordDetail&idt=16534731$$DView record in Pascal Francis$$Hfree_for_read</backlink></links><search><creatorcontrib>Guillén, G.</creatorcontrib><creatorcontrib>Mele, F.D.</creatorcontrib><creatorcontrib>Bagajewicz, M.J.</creatorcontrib><creatorcontrib>Espuña, A.</creatorcontrib><creatorcontrib>Puigjaner, L.</creatorcontrib><title>Multiobjective supply chain design under uncertainty</title><title>Chemical engineering science</title><description>In this article, the design and retrofit problem of a supply chain (SC) consisting of several production plants, warehouses and markets, and the associated distribution systems, is considered. The first problem formulation modifies and extends other previously presented models, in order to include several essential characteristics for realistically representing the consequences of design decisions on the SC performance. Then, in order to take into account the effects of the uncertainty in the production scenario, a two-stage stochastic model is constructed. The problem objective, i.e., SC performance, is assessed by taking into account not only the profit over the time horizon, but also the resulting demand satisfaction. This approach can be used to obtain different kinds of solutions, that may be valuable at different levels. On one hand, the SC configurations obtained by means of deterministic mathematical programming can be compared with those determined by different stochastic scenarios representing different approaches to face uncertainty. Additionally, this approach enables to consider and manage the financial risk associated to the different design options, resulting in a set of Pareto optimal solutions that can be used for decision-making.</description><subject>Applications of mathematics to chemical engineering. Modeling. Simulation. Optimization</subject><subject>Applied sciences</subject><subject>Chemical engineering</subject><subject>Economics. Management. Design assessment</subject><subject>Exact sciences and technology</subject><subject>Optimisation</subject><subject>Risk management</subject><subject>Safety</subject><subject>Supply chain management</subject><issn>0009-2509</issn><issn>1873-4405</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2005</creationdate><recordtype>article</recordtype><recordid>eNp9kD1PwzAQhi0EEqXwA9iywJZwju04FROq-JKKWGC2HOcCjtKk2Eml_nuuaiU2Fp_v9Xsffhi75pBx4MVdmzmMWQ4gKc8gFydsxkstUilBnbIZACzSXMHinF3E2FKqNYcZk29TN_qhatGNfotJnDabbpe4b-v7pMbov_pk6msMdDoMI8nj7pKdNbaLeHWMc_b59PixfElX78-vy4dV6oQqxzTnOejScq3KRQFKcIGVqBq6yIJzbFCjItk2gkyS3mzlXMmthEq6wgoxZ7eHvpsw_EwYR7P20WHX2R6HKZq8VFJDXpCRH4wuDDEGbMwm-LUNO8PB7PmY1hAfs-ezl4gP1dwcm9vobNcE2zsf_woLJaSmnefs_uBD-unWYzDReSQYtQ8EzdSD_2fKL3gAedA</recordid><startdate>20050301</startdate><enddate>20050301</enddate><creator>Guillén, G.</creator><creator>Mele, F.D.</creator><creator>Bagajewicz, M.J.</creator><creator>Espuña, A.</creator><creator>Puigjaner, L.</creator><general>Elsevier Ltd</general><general>Elsevier</general><scope>IQODW</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>8FD</scope><scope>F28</scope><scope>FR3</scope></search><sort><creationdate>20050301</creationdate><title>Multiobjective supply chain design under uncertainty</title><author>Guillén, G. ; Mele, F.D. ; Bagajewicz, M.J. ; Espuña, A. ; Puigjaner, L.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c358t-212078a17589605313eb3bf5314611efe7e5053af38a14eb3abcc81a40b4c6a33</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2005</creationdate><topic>Applications of mathematics to chemical engineering. Modeling. Simulation. Optimization</topic><topic>Applied sciences</topic><topic>Chemical engineering</topic><topic>Economics. Management. Design assessment</topic><topic>Exact sciences and technology</topic><topic>Optimisation</topic><topic>Risk management</topic><topic>Safety</topic><topic>Supply chain management</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Guillén, G.</creatorcontrib><creatorcontrib>Mele, F.D.</creatorcontrib><creatorcontrib>Bagajewicz, M.J.</creatorcontrib><creatorcontrib>Espuña, A.</creatorcontrib><creatorcontrib>Puigjaner, L.</creatorcontrib><collection>Pascal-Francis</collection><collection>CrossRef</collection><collection>Technology Research Database</collection><collection>ANTE: Abstracts in New Technology & Engineering</collection><collection>Engineering Research Database</collection><jtitle>Chemical engineering science</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Guillén, G.</au><au>Mele, F.D.</au><au>Bagajewicz, M.J.</au><au>Espuña, A.</au><au>Puigjaner, L.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Multiobjective supply chain design under uncertainty</atitle><jtitle>Chemical engineering science</jtitle><date>2005-03-01</date><risdate>2005</risdate><volume>60</volume><issue>6</issue><spage>1535</spage><epage>1553</epage><pages>1535-1553</pages><issn>0009-2509</issn><eissn>1873-4405</eissn><coden>CESCAC</coden><abstract>In this article, the design and retrofit problem of a supply chain (SC) consisting of several production plants, warehouses and markets, and the associated distribution systems, is considered. The first problem formulation modifies and extends other previously presented models, in order to include several essential characteristics for realistically representing the consequences of design decisions on the SC performance. Then, in order to take into account the effects of the uncertainty in the production scenario, a two-stage stochastic model is constructed. The problem objective, i.e., SC performance, is assessed by taking into account not only the profit over the time horizon, but also the resulting demand satisfaction. This approach can be used to obtain different kinds of solutions, that may be valuable at different levels. On one hand, the SC configurations obtained by means of deterministic mathematical programming can be compared with those determined by different stochastic scenarios representing different approaches to face uncertainty. Additionally, this approach enables to consider and manage the financial risk associated to the different design options, resulting in a set of Pareto optimal solutions that can be used for decision-making.</abstract><cop>Oxford</cop><pub>Elsevier Ltd</pub><doi>10.1016/j.ces.2004.10.023</doi><tpages>19</tpages></addata></record> |
fulltext | fulltext |
identifier | ISSN: 0009-2509 |
ispartof | Chemical engineering science, 2005-03, Vol.60 (6), p.1535-1553 |
issn | 0009-2509 1873-4405 |
language | eng |
recordid | cdi_proquest_miscellaneous_28547026 |
source | ScienceDirect Journals |
subjects | Applications of mathematics to chemical engineering. Modeling. Simulation. Optimization Applied sciences Chemical engineering Economics. Management. Design assessment Exact sciences and technology Optimisation Risk management Safety Supply chain management |
title | Multiobjective supply chain design under uncertainty |
url | http://sfxeu10.hosted.exlibrisgroup.com/loughborough?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-05T08%3A57%3A11IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_cross&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Multiobjective%20supply%20chain%20design%20under%20uncertainty&rft.jtitle=Chemical%20engineering%20science&rft.au=Guill%C3%A9n,%20G.&rft.date=2005-03-01&rft.volume=60&rft.issue=6&rft.spage=1535&rft.epage=1553&rft.pages=1535-1553&rft.issn=0009-2509&rft.eissn=1873-4405&rft.coden=CESCAC&rft_id=info:doi/10.1016/j.ces.2004.10.023&rft_dat=%3Cproquest_cross%3E28547026%3C/proquest_cross%3E%3Cgrp_id%3Ecdi_FETCH-LOGICAL-c358t-212078a17589605313eb3bf5314611efe7e5053af38a14eb3abcc81a40b4c6a33%3C/grp_id%3E%3Coa%3E%3C/oa%3E%3Curl%3E%3C/url%3E&rft_id=info:oai/&rft_pqid=28547026&rft_id=info:pmid/&rfr_iscdi=true |