Fuzzy multi objective supply chain design considering facility disruptions, supply and demand risks by uncertainty in economic parameters
In this paper, supply chain network design problem is modeled as a fuzzy multi objective mixed integer programming which seeks to locate the plants, DCs, and warehouses by considering disruption, supply and demand risk. Maximizing net present value of supply chain cash flow, minimizing delivery tard...
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doaj-b7839f2b0e634702aeb3b944b099805a2020-11-24T22:16:57ZfasAllameh Tabataba'i University PressMuṭāli̒āt-i Mudīriyyat-i Ṣan̒atī2251-80292015-07-011337535Fuzzy multi objective supply chain design considering facility disruptions, supply and demand risks by uncertainty in economic parametersAmir Farshbaf-GeranmayehNeda ManavizadehMasoud RabbaniIn this paper, supply chain network design problem is modeled as a fuzzy multi objective mixed integer programming which seeks to locate the plants, DCs, and warehouses by considering disruption, supply and demand risk. Maximizing net present value of supply chain cash flow, minimizing delivery tardiness and maximizing reliability of suppliers are considered as objective functions in the proposed mathematic model. In order to have a more reliable model in case of disruption, the robustness measure is used in the model. Moreover, because of the lack of information, the economic factors such as tax rate, interest rate, and inflation are considered as uncertain factors in the model. An interactive possibilistic programming approach is applied for solving the multi-objective model. To solve larger size instances, genetic algorithm is proposed. Finally numerical examples are presented to show how the model works in practice http://jims.atu.ac.ir/article_1312_f6ba2d6c1b6bafaf1f592fd3e62e4e71.pdfSupply Chain Design; Multi Objective Programming; Possibilistic Programming; Business Cash Flow; TH Method; Genetic Algorithm |
collection |
DOAJ |
language |
fas |
format |
Article |
sources |
DOAJ |
author |
Amir Farshbaf-Geranmayeh Neda Manavizadeh Masoud Rabbani |
spellingShingle |
Amir Farshbaf-Geranmayeh Neda Manavizadeh Masoud Rabbani Fuzzy multi objective supply chain design considering facility disruptions, supply and demand risks by uncertainty in economic parameters Muṭāli̒āt-i Mudīriyyat-i Ṣan̒atī Supply Chain Design; Multi Objective Programming; Possibilistic Programming; Business Cash Flow; TH Method; Genetic Algorithm |
author_facet |
Amir Farshbaf-Geranmayeh Neda Manavizadeh Masoud Rabbani |
author_sort |
Amir Farshbaf-Geranmayeh |
title |
Fuzzy multi objective supply chain design considering facility disruptions, supply and demand risks by uncertainty in economic parameters |
title_short |
Fuzzy multi objective supply chain design considering facility disruptions, supply and demand risks by uncertainty in economic parameters |
title_full |
Fuzzy multi objective supply chain design considering facility disruptions, supply and demand risks by uncertainty in economic parameters |
title_fullStr |
Fuzzy multi objective supply chain design considering facility disruptions, supply and demand risks by uncertainty in economic parameters |
title_full_unstemmed |
Fuzzy multi objective supply chain design considering facility disruptions, supply and demand risks by uncertainty in economic parameters |
title_sort |
fuzzy multi objective supply chain design considering facility disruptions, supply and demand risks by uncertainty in economic parameters |
publisher |
Allameh Tabataba'i University Press |
series |
Muṭāli̒āt-i Mudīriyyat-i Ṣan̒atī |
issn |
2251-8029 |
publishDate |
2015-07-01 |
description |
In this paper, supply chain network design problem is modeled as a fuzzy multi objective mixed integer programming which seeks to locate the plants, DCs, and warehouses by considering disruption, supply and demand risk. Maximizing net present value of supply chain cash flow, minimizing delivery tardiness and maximizing reliability of suppliers are considered as objective functions in the proposed mathematic model. In order to have a more reliable model in case of disruption, the robustness measure is used in the model. Moreover, because of the lack of information, the economic factors such as tax rate, interest rate, and inflation are considered as uncertain factors in the model. An interactive possibilistic programming approach is applied for solving the multi-objective model. To solve larger size instances, genetic algorithm is proposed. Finally numerical examples are presented to show how the model works in practice
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topic |
Supply Chain Design; Multi Objective Programming; Possibilistic Programming; Business Cash Flow; TH Method; Genetic Algorithm |
url |
http://jims.atu.ac.ir/article_1312_f6ba2d6c1b6bafaf1f592fd3e62e4e71.pdf |
work_keys_str_mv |
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